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IntroductionEither non-invasive somatotopic or substitute sensory feedback is capable of conveying a single modality of sensory information from prosthetic hands to amputees. However, the neurocognitive ability of amputees to integrate multi-modality sensory information for functional discrimination is unclear. The purpose of this study was to assess the fusion of non-invasive somatotopic tactile and substitute aperture feedbacks for profile perception of multiple physical features during grasping objects.MethodsTwo left transradial amputees with somatotopic evoked tactile sensation (ETS) of five fingers participated in the study. The tactile information of prosthetic hand was provided to amputees by the ETS feedback elicited on the stump projected finger map. Hand aperture information was conveyed to amputees with substitute electrotactile stimulation on the forearm or upper arm. Two types of sensory feedback were integrated to a commercial prosthetic hand. The efficacy of somatotopic ETS feedback on object length identification task was assessed with or without substitute aperture stimulation. The object size identification task was utilized to assess how ETS stimulation at the stump may affect aperture perception with stimulation on the ipsilateral upper arm or forearm. Finally, the task of identifying combined length and size was conducted to evaluate the ability of amputees to integrate the dual modalities of sensory feedback for perceiving profile features.ResultsThe study revealed that amputee subjects can effectively integrate the ETS feedback with electrotactile substitutive feedback for object profile discrimination. Specifically, ETS was robust to provide object length information with electrotactile stimulation at either the forearm or upper arm. However, electrotactile stimulation at the upper arm for aperture perception was less susceptible to the interference of ETS stimulation than at the forearm.DiscussionAmputee subjects are able to combine somatotopic ETS and aperture feedbacks for identifying multi-dimensional features in object profiling. The two sensory streams of information can be fused effectively without mutual interference for functional discrimination.

The lack of intuitive and active human–robot interaction makes it difficult to use upper-limb-assistive devices. In this paper, we propose a novel learning-based controller that intuitively uses onset motion to predict the desired end-point position for an assistive robot. A multi-modal sensing system comprising inertial measurement units (IMUs), electromyographic (EMG) sensors, and mechanomyography (MMG) sensors was implemented. This system was used to acquire kinematic and physiological signals during reaching and placing tasks performed by five healthy subjects. The onset motion data of each motion trial were extracted to input into traditional regression models and deep learning models for training and testing. The models can predict the position of the hand in planar space, which is the reference position for low-level position controllers. The results show that using IMU sensor with the proposed prediction model is sufficient for motion intention detection, which can provide almost the same prediction performance compared with adding EMG or MMG. Additionally, recurrent neural network (RNN)-based models can predict target positions over a short onset time window for reaching motions and are suitable for predicting targets over a longer horizon for placing tasks. This study's detailed analysis can improve the usability of the assistive/rehabilitation robots. [ABSTRACT FROM AUTHOR]

Purpose: To analyze the efficacy of fusional vergence therapy (FVT) in management of consecutive esotropia with diplopia after intermittent exotropia (IXT) surgery. The current study is carried on how FVT affects the duration of treatment, sensory fusion, and exotropic drift. Methods: This was a retrospective study for the medical record of 11 patients with consecutive esotropia after IXT surgery of 543 patients over the period of 5 year, with mean surgery age of 9.5 (range: 4–33 y). FVT was planned after minimum 6 weeks of surgery and was considered for maximum 24 weeks. Patients underwent a combination of office-based and home-based FVT. Successful outcome of therapy was considered where diplopia resolves in free space and achieves sensory fusion, stereopsis with no manifest deviation. Results: Record of 543 patients who had horizontal muscle surgery for IXT were identified and reviewed. Records of 11 patients who showed consecutive esotropia of 10 prism diopter (PD) or more with normal retinal correspondence, with or without diplopia complaint, after 6 week of surgery and had undergone vision therapy management were reviewed. A successful outcome of binocular single vision with good sensory and motor fusion with no manifest deviation or prism requirement was achieved with in the mean duration of 4.8 month of therapy. With a mean duration of 4 weeks of therapy, the mean angle of deviation reduced by 53% for distance (17 PD to 8 PD) and 27% for near (11 PD to 8 PD) and mean stereopsis improvement by 80% with 94% patients demonstrating sensory fusion on Bagolini test and 94% of patients having no symptoms of diplopia or squint. Conclusion: With nonsurgical management involving refractive error correction, FVT, and prism, consecutive esotropia was resolved in 74% cases. Management of consecutive esotropia with FVT can result in satisfactory sensory fusion and successful motor alignment.

Purpose: To analyze the efficacy of fusional vergence therapy (FVT) in management of consecutive esotropia with diplopia after intermittent exotropia (IXT) surgery. The current study is carried on how FVT affects the duration of treatment, sensory fusion, and exotropic drift.Methods: This was a retrospective study for the medical record of 11 patients with consecutive esotropia after IXT surgery of 543 patients over the period of 5 year, with mean surgery age of 9.5 (range: 4-33 y). FVT was planned after minimum 6 weeks of surgery and was considered for maximum 24 weeks. Patients underwent a combination of office-based and home-based FVT. Successful outcome of therapy was considered where diplopia resolves in free space and achieves sensory fusion, stereopsis with no manifest deviation.Results: Record of 543 patients who had horizontal muscle surgery for IXT were identified and reviewed. Records of 11 patients who showed consecutive esotropia of 10 prism diopter (PD) or more with normal retinal correspondence, with or without diplopia complaint, after 6 week of surgery and had undergone vision therapy management were reviewed. A successful outcome of binocular single vision with good sensory and motor fusion with no manifest deviation or prism requirement was achieved with in the mean duration of 4.8 month of therapy. With a mean duration of 4 weeks of therapy, the mean angle of deviation reduced by 53% for distance (17 PD to 8 PD) and 27% for near (11 PD to 8 PD) and mean stereopsis improvement by 80% with 94% patients demonstrating sensory fusion on Bagolini test and 94% of patients having no symptoms of diplopia or squint.Conclusion: With nonsurgical management involving refractive error correction, FVT, and prism, consecutive esotropia was resolved in 74% cases. Management of consecutive esotropia with FVT can result in satisfactory sensory fusion and successful motor alignment. [ABSTRACT FROM AUTHOR]

Executing agile locomotion requires animals to integrate sensory feedback, often from multiple sources. For example, human gaze is mediated by multiple feedback loops that integrate visual and vestibular information. A central challenge in studying biological feedback loops is that they are nested and dynamically coupled. Here, we develop a framework based on control theory for unraveling nested feedback systems and apply it to study gaze stabilization in the fruit fly (Drosophila). By combining experimental and mathematical methods to manipulate control topologies, we uncovered the role of body-generated mechanosensory feedback nested within visual feedback in the control of head movements. We discovered that visual feedback changed the tuning of head movements across visual motion frequencies whereas mechanosensory feedback damped head movements. Head saccades had slower dynamics when the body was free to move, further pointing to the role of damping via mechanosensory feedback. By comparing head responses between self-generated and externally generated body motion, we revealed a nonlinear gating of mechanosensory feedback that is motor-context dependent. Altogether, our findings reveal the role of nested feedback loops in flies and uncover mechanisms that reconcile differences in head kinematics between body-free and body-fixed flies. Our framework is generalizable to biological and robotic systems relying on nested feedback control for guiding locomotion.

The lack of intuitive and active human–robot interaction makes it difficult to use upper-limb-assistive devices. In this paper, we propose a novel learning-based controller that intuitively uses onset motion to predict the desired end-point position for an assistive robot. A multi-modal sensing system comprising inertial measurement units (IMUs), electromyographic (EMG) sensors, and mechanomyography (MMG) sensors was implemented. This system was used to acquire kinematic and physiological signals during reaching and placing tasks performed by five healthy subjects. The onset motion data of each motion trial were extracted to input into traditional regression models and deep learning models for training and testing. The models can predict the position of the hand in planar space, which is the reference position for low-level position controllers. The results show that using IMU sensor with the proposed prediction model is sufficient for motion intention detection, which can provide almost the same prediction performance compared with adding EMG or MMG. Additionally, recurrent neural network (RNN)-based models can predict target positions over a short onset time window for reaching motions and are suitable for predicting targets over a longer horizon for placing tasks. This study’s detailed analysis can improve the usability of the assistive/rehabilitation robots.

In the modern world; technology is the asset of the development. There is demand of automation in every sector. Such type of autonomous applications requires inputs from multiple sensory resources and based on these inputs it processes and deliver intelligent decision i.e. output. The method used in proposed system focuses on collection of sensory information and few concluding parameters derivations from data which will help to decide taking best decisions for autonomous applications. Drawing conclusion based on only one aspect is not effective as compared to conclusions taken from many other heterogeneous sensors parameters. This system fulfills parameters such as accuracy, less request time and response time, performance, reliability etc. This paper explains safe and secure system which uses unsupervised algorithm that works on real time data and mixes the information from various resources. The main interest is by taking intelligent decision based on reduction of unreliability and disordered sensory data. Women being a major victim in today's world with their entry in almost each field their safety is a priority and with our concept and algorithm we have illustrated it as a system for sensory fusion with GPS enabled double security feature which will help a women when she feels insecure or harassed or in a difficult situation. System has smart feature to ensure complete safety of women even in dangerous situation where she cannot turn on the trigger. The system comprises of ATmega328P microcontroller, GPS, LCD display, fingerprint module, GPS, GSM etc. for proper and accurate working of the system to provide reliable, accurate and quickservice which efficiently work for safety of women. [ABSTRACT FROM AUTHOR]

We describe a new unified model to explain both binocular fusion and depth perception, over a broad range of depths. At each location, the model consists of an array of paired spatial frequency filters, with different relative horizontal shifts (position disparity) and interocular phase disparities of 0, 90, ±180, or -90°. The paired filters with different spatial profiles (non-zero phase disparity) compute interocular misalignment and provide phase-disparity energy (binocular fusion energy) to drive selection of the appropriate filters along the position disparity space until the misalignment is eliminated and sensory fusion is achieved locally. The paired filters with identical spatial profiles (0 phase disparity) compute the position-disparity energy. After sensory fusion, the combination of position and possible residual phase disparity energies is calculated for binocular depth perception. Binocular fusion occurs at multiple scales following a coarse-to-fine process. At a given location, the apparent depth is the weighted sum of fusion shifts combined with residual phase disparity in all spatial-frequency channels, and the weights depend on stimulus spatial frequency and stimulus contrast. To test the theory, we measured disparity minimum and maximum thresholds (Dmin and Dmax) at three spatial frequencies and with different intraocular contrast levels. The stimuli were Random-Gabor-Patch (RGP) stereograms consisting of Gabor patches with random positions and phases, but with a fixed spatial frequency. The two eyes viewed identical arrays of patches except that one eye's array could be shifted horizontally and could differ in contrast. Our experiments and modeling reveal two contrast normalization mechanisms: (1) Energy Normalization (EN): Binocular energy is normalized with monocular energy after the site of binocular combination. This predicts constant Dmin thresholds when varying stimulus contrast in the two eyes; (2) DSKL model Interocular interactions: Monocular contrasts are normalized before the binocular combination site through interocular contrast gain-control and gain-enhancement mechanisms. This predicts contrast dependent Dmax thresholds. We tested a range of models and found that a model consisting of a second-order pathway with DSKL interocular interactions and a first-order pathway with EN at each spatial-frequency band can account for both the Dmin and Dmax data very well. Simulations show that the model makes reasonable predictions of suprathreshold depth perception. [ABSTRACT FROM AUTHOR]

We propose a novel controller for powered prosthetic arms, where fused EMG and gaze data predict the desired end-point for a full arm prosthesis, which could drive the forward motion of individual joints. We recorded EMG, gaze, and motion-tracking during pick-and-place trials with 7 able-bodied subjects. Subjects positioned an object above a random target on a virtual interface, each completing around 600 trials. On average across all trials and subjects gaze preceded EMG and followed a repeatable pattern that allowed for prediction. A computer vision algorithm was used to extract the initial and target fixations and estimate the target position in 2D space. Two SVRs were trained with EMG data to predict the x- and y- position of the hand; results showed that the y-estimate was significantly better than the x-estimate. The EMG and gaze predictions were fused using a Kalman Filter-based approach, and the positional error from using EMG-only was significantly higher than the fusion of EMG and gaze. The final target position Root Mean Squared Error (RMSE) decreased from 9.28 cm with an EMG-only prediction to 6.94 cm when using a gaze-EMG fusion. This error also increased significantly when removing some or all arm muscle signals. However, using fused EMG and gaze, there were no significant difference between predictors that included all muscles, or only a subset of muscles. [ABSTRACT FROM AUTHOR]

The work presents real-time data acquisition and monitoring for environmental sensors. This paper presents data fetching and processing implemented by modern approaches of Python. A functional diagram of a materialized system and algorithmic diagrams for Python 3 implemented programs are given. The functionality of the programmed system has been checked by testing the implemented program structures and performing experiments under different environmental conditions with actual results obtained. [ABSTRACT FROM AUTHOR]

Aims: Bagolini striated lenses are a useful test of binocular vision, but the variations in the striations (frequency and thickness) can impact on the perceived image. Also, responses can be difficult to interpret in young children. Therefore, the aims of this project were to evaluate the impact of striation frequency and the addition of coloured filters on subjective responses. Methods: Three sets of striated lenses were made (small, medium and large striations), each produced in two forms (both lenses clear, or with a red and blue lens). Also, Bagolini glasses (Optiker Ryser) were used, with and without the addition of red and blue filters. Subjects were asked to report what they perceived, with subsequent questions regarding the number and length of lines. Results: Forty-two adult subjects were tested, with uniocular VA ranging from –0.18 to 1.10 logMAR (mean 0.08 ± 0.25). The number of lines seen when varying the line thickness did not vary between coloured and clear lenses (post-hoc analysis following ANOVA, p > 0.1 in all comparisons). Adding red/blue filters to the original Bagolini glasses did not alter the rates of subjects perceiving a cross (Chi-square, p = 0.8). However, the laser-cut lenses produced a significantly shorter light streak than the original lenses (One-way ANOVA, p < 0.001), but the colour of the filters made no difference to the length of streak perceived (Tukey’s Test, p = 0.20). Conclusions: The addition of coloured filters did not impact on the responses given to the original or laser-cut lenses, suggesting this modification may aid responses in children. However, further evaluation is required with finer striations and thinner lenses to improve the visibility of the lines.

Introduction: Either non-invasive somatotopic or substitute sensory feedback is capable of conveying a single modality of sensory information from prosthetic hands to amputees. However, the neurocognitive ability of amputees to integrate multi-modality sensory information for functional discrimination is unclear. The purpose of this study was to assess the fusion of non-invasive somatotopic tactile and substitute aperture feedbacks for profile perception of multiple physical features during grasping objects., Methods: Two left transradial amputees with somatotopic evoked tactile sensation (ETS) of five fingers participated in the study. The tactile information of prosthetic hand was provided to amputees by the ETS feedback elicited on the stump projected finger map. Hand aperture information was conveyed to amputees with substitute electrotactile stimulation on the forearm or upper arm. Two types of sensory feedback were integrated to a commercial prosthetic hand. The efficacy of somatotopic ETS feedback on object length identification task was assessed with or without substitute aperture stimulation. The object size identification task was utilized to assess how ETS stimulation at the stump may affect aperture perception with stimulation on the ipsilateral upper arm or forearm. Finally, the task of identifying combined length and size was conducted to evaluate the ability of amputees to integrate the dual modalities of sensory feedback for perceiving profile features., Results: The study revealed that amputee subjects can effectively integrate the ETS feedback with electrotactile substitutive feedback for object profile discrimination. Specifically, ETS was robust to provide object length information with electrotactile stimulation at either the forearm or upper arm. However, electrotactile stimulation at the upper arm for aperture perception was less susceptible to the interference of ETS stimulation than at the forearm., Discussion: Amputee subjects are able to combine somatotopic ETS and aperture feedbacks for identifying multi-dimensional features in object profiling. The two sensory streams of information can be fused effectively without mutual interference for functional discrimination., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. The author(s) declared that they were an editorial board member of Frontiers, at the time of submission. This had no impact on the peer review process and the final decision., (Copyright © 2023 Zhang, Chou, Hao, Li, Yu and Lan.)

Restoring locomotion functionality of transfemoral amputees is essential for early rehabilitation treatment and for preserving mobility and independence in daily life. Research in wearable robotics fostered the development of innovative active mechatronic lower-limb prostheses designed with the goal to reduce the cognitive and physical effort of lower-limb amputees in rehabilitation and daily life activities. To ensure benefits to the users, active mechatronic prostheses are expected to be aware of the user intention and properly interact in a closed human-in-the-loop paradigm. In the state of the art various cognitive interfaces have been proposed to online decode the user's intention. Electromyography in combination with mechanical sensing such as inertial or pressure sensors is a widely adopted solution for driving active mechatronic prostheses. In this framework, researchers also explored targeted muscles re-innervation for an objective-oriented surgical amputation promoting wider usability of active prostheses. However, information kept by the neural component of the cognitive interface deteriorates in a prolonged use scenario due to electrodes-related issues, thereby undermining the correct functionality of the active prosthesis. The objective of this work is to present a novel controller for an active transfemoral prosthesis based on whole body awareness relying on a wireless distributed non-invasive sensory apparatus acting as cognitive interface. A finite-state machine controller based on signals monitored from the wearable interface performs subject-independent intention detection of functional tasks such as ground level walking, stair ascent, and sit-to-stand maneuvres and their main sub-phases. Experimental activities carried out with four transfemoral amputees (among them one dysvascular) demonstrated high reliability of the controller capable of providing 100% accuracy rate in treadmill walking even for weak subjects and low walking speeds. The minimum success rate was of 94.8% in performing sit-to-stand tasks. All the participants showed high confidence in using the transfemoral active prosthesis even without training period thanks to intuitiveness of the whole body awareness controller.

The direction of the Earth’s magnetic field is used as a reference vector to determine the heading in orientation estimation with wearable sensors. However, the magnetic field strength is weak and can be easily disturbed in the vicinity of ferromagnetic materials, which may result in inaccurate estimate of orientation. This paper presents a novel method for estimating and compensating for magnetic disturbances. The compensation algorithm is implemented within a kinematic-based extended Kalman filter and is based on an assessment of the magnetic disturbance and the change of orientation in each time step. The proposed algorithm was experimentally validated by measuring the orientation of a simple mechanical system with three degrees of freedom in an artificially disturbed magnetic field. The results of the experimental evaluation show that an Kalman filter algorithm that incorporates compensating for magnetic disturbances is capable of estimating the orientation with moderate error (the absolute median errors \Delta \widetilde \theta X,\Delta \widetilde \theta Z < {2}^{\circ } , \Delta \widetilde \theta Y < {9}^{\circ } ) when the Earth’s magnetic field is disturbed by magnetic disturbance with a magnitude equal to twice the magnitude of the Earth’s own magnetic field in different directions. [ABSTRACT FROM PUBLISHER]

Restoring locomotion functionality of transfemoral amputees is essential for early rehabilitation treatment and for preserving mobility and independence in daily life. Research in wearable robotics fostered the development of innovative activemechatronic lower-limb prostheses designed with the goal to reduce the cognitive and physical effort of lower-limb amputees in rehabilitation and daily life activities. To ensure benefits to the users, active mechatronic prostheses are expected to be aware of the user intention and properly interact in a closed human-in-the-loop paradigm. In the state of the art various cognitive interfaces have been proposed to online decode the user's intention. Electromyography in combination with mechanical sensing such as inertial or pressure sensors is a widely adopted solution for driving active mechatronic prostheses. In this framework, researchers also explored targeted muscles re-innervation for an objective-oriented surgical amputation promoting wider usability of active prostheses. However, information kept by the neural component of the cognitive interface deteriorates in a prolonged use scenario due to electrodes-related issues, thereby undermining the correct functionality of the active prosthesis. The objective of this work is to present a novel controller for an active transfemoral prosthesis based on whole body awareness relying on a wireless distributed non-invasive sensory apparatus acting as cognitive interface. A finite-state machine controller based on signals monitored from the wearable interface performs subject-independent intention detection of functional tasks such as ground level walking, stair ascent, and sit-to-stand maneuvres and their main sub-phases. Experimental activities carried out with four transfemoral amputees (among them one dysvascular) demonstrated high reliability of the controller capable of providing 100%accuracy rate in treadmill walking even for weak subjects and low walking speeds. The minimum success rate was of 94.8% in performing sit-to-stand tasks. All the participants showed high confidence in using the transfemoral active prosthesis even without training period thanks to intuitiveness of the whole body awareness controller. [ABSTRACT FROM AUTHOR]

This work proposes a new methodology for the detection of discontinuities in the weld bead applied in Shielded Metal ArcWelding (SMAW) processes. The detection system is based on two sensors--a microphone and piezoelectric--that acquire acoustic emissions generated during the welding. The feature vectors extracted from the sensor dataset are used to construct classifier models. The approaches based on Artificial Neural Network (ANN) and Support Vector Machine (SVM) classifiers are able to identify with a high accuracy the three proposed weld bead classes: desirable weld bead, shrinkage cavity and burn through discontinuities. Experimental results illustrate the system's high accuracy, greater than 90% for each class. A novel Hierarchical Support Vector Machine (HSVM) structure is proposed to make feasible the use of this system in industrial environments. This approach presented 96.6% overall accuracy. Given the simplicity of the equipment involved, this system can be applied in the metal transformation industries. [ABSTRACT FROM AUTHOR]

This work investigates an over-arching question: how can an immersive virtual environment be connected with its intelligent physical counterpart to allow for a more efficient man-machine collaboration. To this end, an immersive user interface for the purpose of robot tele-operation is designed. A large amount of sensory data is utilized to build models of the world and its inhabitants in a way that is intuitive to the operator and accurately represents the robot’s real-world state and environment. The game client is capable of handling multiple users, much like a traditional multiplayer game, while visualizing multiple robotic agents operating within the real world. The proposed Virtual Environment for Tele-Operation (VETO) architecture is a tele-operation system that provides a feature-rich framework to implement robotic agents into an immersive end-user game interface. Game levels are generated dynamically on a Graphic Processing Unit or GPU-accelerated server based on real-world sensor data from the robotic agents. A set of user studies are conducted to validate the performance of the proposed architecture compared to traditional tele-robotic applications. The experimental results show significant improvements in both task completion time and task completion rate over traditional tools.

Aim: To determine whether the level of sensory fusion in normal participants is affected significantly by fixation light intensity. Methods: Seventeen normal adult participants had sensory fusion measurements taken using the Sbisa bar, combined with Bagolini glasses, as a control for binocular single vision, whilst fixating lights of three different intensities: 150 lux, 250 lux and 350 lux. Data were analysed using Friedman’s test and the Wilcoxon matched pairs signed ranks test. Results: Seventeen participants were tested (mean 35.3 years, range 23–60 years). Friedman’s test showed at least two of the light intensities had a statistically significant effect upon sensory fusion results ( p = 0.011). Wilcoxon matched pairs signed rank testing found no statistically significant difference in levels of sensory fusion when fixating the 150 lux and 250 lux fixation lights ( p = 0.194). There was a statistically significant difference in the level of sensory fusion when fixating the 150 lux and 350 lux lights ( p = 0.011) and the 250 lux and 350 lux lights ( p = 0.017). Conclusion: Changing the intensity of the fixation light from 150 lux to 350 lux and from 250 lux to 350 lux significantly affected the level of sensory fusion measured. The higher the intensity of the light, the greater the filter needed to break fusion. The clinical significance of these results is considered.

Deep Belief Networks (DBNs) have recently shown impressive performance on a broad range of classification problems. Their generative properties allow better understanding of the performance, and provide a simpler solution for sensor fusion tasks. However, because of their inherent need for feedback and parallel update of large numbers of units, DBNs are expensive to implement on serial computers. This paper proposes a method based on the Siegert approximation for Integrate-and-Fire neurons to map an offline-trained DBN onto an efficient event-driven spiking neural network suitable for hardware implementation. The method is demonstrated in simulation and by a real-time implementation of a 3-layer network with 2694 neurons used for visual classification of MNIST handwritten digits with input from a 128x128 Dynamic Vision Sensor (DVS) silicon retina, and sensory-fusion using additional input from a 64-channel AER-EAR silicon cochlea. The system is implemented through the open-source software in the jAER project and runs in real-time on a laptop computer. It is demonstrated that the system can recognize digits in the presence of distractions, noise, scaling, translation and rotation, and that the degradation of recognition performance by using an event-based approach is less than 1%. Recognition is achieved in an average of 5.8 ms after the onset of the presentation of a digit. By cue integration from both silicon retina and cochlea outputs we show that the system can be biased to select the correct digit from otherwise ambiguous input.

Abstract: Measuring the kinematic parameters in unconstrained human motion is becoming crucial for providing feedback information in wearable robotics and sports monitoring. This paper presents a novel sensory fusion algorithm for assessing the orientations of human body segments in long-term human walking based on signals from wearable sensors. The basic idea of the proposed algorithm is to constantly fuse the measured segment's angular velocity and linear acceleration via known kinematic relations between segments. The wearable sensory system incorporates seven inertial measurement units attached to the human body segments and two instrumented shoe insoles. The proposed system was experimentally validated in a long-term walking on a treadmill and on a polygon with stairs simulating different activities in everyday life. The outputs were compared to the reference parameters measured by a stationary optical system. Results show accurate joint angle measurements (error median below 5°) in all evaluated walking conditions with no expressed drift over time. [Copyright &y& Elsevier]

Abstract: Surface electrical potential and observational growth recordings were made of a protoplasmic tube of the slime mould Physarum polycephalum in response to a multitude of stimuli with regards to sensory fusion or multisensory integration. Each stimulus was tested alone and in combination in order to evaluate for the first time the effect that multiple stimuli have on the frequency of streaming oscillation. White light caused a decrease in frequency whilst increasing the temperature and applying a food source in the form of oat flakes both increased the frequency. Simultaneously stimulating P. polycephalum with light and oat flake produced no net change in frequency, while combined light and heat stimuli showed an increase in frequency smaller than that observed for heat alone. When the two positive stimuli, oat flakes and heat, were combined, there was a net increase in frequency similar to the cumulative increases caused by the individual stimuli. Boolean logic gates were derived from the measured frequency change. [Copyright &y& Elsevier]

Flies and other insects use vision to regulate their groundspeed in flight, enabling them to fly in varying wind conditions. Compared with mechanosensory modalities, however, vision requires a long processing delay (~100 ms) that might introduce instability if operated at high gain. Flies also sense air motion with their antennae, but how this is used in flight control is unknown. We manipulated the antennal function of fruit flies by ablating their aristae, forcing them to rely on vision alone to regulate groundspeed. Arista-ablated flies in flight exhibited significantly greater groundspeed variability than intact flies. We then subjected them to a series of controlled impulsive wind gusts delivered by an air piston and experimentally manipulated antennae and visual feedback. The results show that an antenna-mediated response alters wing motion to cause flies to accelerate in the same direction as the gust. This response opposes flying into a headwind, but flies regularly fly upwind. To resolve this discrepancy, we obtained a dynamic model of the fly's velocity regulator by fitting parameters of candidate models to our experimental data. The model suggests that the groundspeed variability of arista-ablated flies is the result of unstable feedback oscillations caused by the delay and high gain of visual feedback. The antenna response drives active damping with a shorter delay (~20 ms) to stabilize this regulator, in exchange for increasing the effect of rapid wind disturbances. This provides insight into flies' multimodal sensory feedback architecture and constitutes a previously unknown role for the antennae. [ABSTRACT FROM AUTHOR]

Deep Belief Networks (DBNs) have recently shown impressive performance on a broad range of classification problems. Their generative properties allow better understanding of the performance, and provide a simpler solution for sensor fusion tasks. However, because of their inherent need for feedback and parallel update of large numbers of units, DBNs are expensive to implement on serial computers. This paper proposes a method based on the Siegert approximation for Integrate-and-Fire neurons to map an offline-trained DBN onto an efficient event-driven spiking neural network suitable for hardware implementation. The method is demonstrated in simulation and by a real-time implementation of a 3-layer network with 2694 neurons used for visual classification of MNIST handwritten digits with input from a 128 × 128 Dynamic Vision Sensor (DVS) silicon retina, and sensoryfusion using additional input from a 64-channel AER-EAR silicon cochlea. The system is implemented through the open-source software in the jAER project and runs in real-time on a laptop computer. It is demonstrated that the system can recognize digits in the presence of distractions, noise, scaling, translation and rotation, and that the degradation of recognition performance by using an event-based approach is less than 1%. Recognition is achieved in an average of 5.8 ms after the onset of the presentation of a digit. By cue integration from both silicon retina and cochlea outputs we show that the system can be biased to select the correct digit from otherwise ambiguous input. [ABSTRACT FROM AUTHOR]

Executing agile locomotion requires animals to integrate sensory feedback, often from multiple sources. For example, human gaze is mediated by multiple feedback loops that integrate visual and vestibular information. A central challenge in studying biological feedback loops is that they are nested and dynamically coupled. Here, we develop a framework based on control theory for unraveling nested feedback systems and apply it to study gaze stabilization in the fruit fly ( Drosophila ). By combining experimental and mathematical methods to manipulate control topologies, we uncovered the role of body-generated mechanosensory feedback nested within visual feedback in the control of head movements. We discovered that visual feedback changed the tuning of head movements across visual motion frequencies whereas mechanosensory feedback damped head movements. Head saccades had slower dynamics when the body was free to move, further pointing to the role of damping via mechanosensory feedback. By comparing head responses between self-generated and externally generated body motion, we revealed a nonlinear gating of mechanosensory feedback that is motor-context dependent. Altogether, our findings reveal the role of nested feedback loops in flies and uncover mechanisms that reconcile differences in head kinematics between body-free and body-fixed flies. Our framework is generalizable to biological and robotic systems relying on nested feedback control for guiding locomotion., Competing Interests: BC, JM No competing interests declared, (© 2022, Cellini and Mongeau.)

Most conventional robots rely on controlling the location of the center of pressure to maintain balance, relying mainly on foot pressure sensors for information. By contrast, humans rely on sensory data from multiple sources, including proprioceptive, visual, and vestibular sources. Several models have been developed to explain how humans reconcile information from disparate sources to form a stable sense of balance. These models may be useful for developing robots that are able to maintain dynamic balance more readily using multiple sensory sources. Since these information sources may conflict, reliance by the nervous system on any one channel can lead to ambiguity in the system state. In humans, experiments that create conflicts between different sensory channels by moving the visual field or the support surface indicate that sensory information is adaptively reweighted. Unreliable information is rapidly down-weighted, then gradually up-weighted when it becomes valid again. Human balance can also be studied by building robots that model features of human bodies and testing them under similar experimental conditions. We implement a sensory reweighting model based on an adaptive Kalman filter in a bipedal robot, and subject it to sensory tests similar to those used on human subjects. Unlike other implementations of sensory reweighting in robots, our implementation includes vision, by using optic flow to calculate forward rotation using a camera (visual modality), as well as a three-axis gyro to represent the vestibular system (non-visual modality), and foot pressure sensors (proprioceptive modality). Our model estimates measurement noise in real time, which is then used to recompute the Kalman gain on each iteration, improving the ability of the robot to dynamically balance. We observe that we can duplicate many important features of postural sway in humans, including automatic sensory reweighting, effects, constant phase with respect to amplitude, and a temporal asymmetry in the reweighting gains. [ABSTRACT FROM AUTHOR]

Purpose: Anisometropia is reported to increase with age; however, the relationship between the development of anisometropia and binocular vision has not been determined. The purpose of this study was to determine the relationship between anisometropia and binocular vision after esotropia (ET) surgery. Methods: The medical records of 51 consecutive patients with ET who had undergone ET surgery were studied. Patients with amblyopia or anisometropia ≥2 diopters (D) before surgery were excluded. The average age of the patients at the time of surgery was 4.5 ± 3.7 years, and the average postoperative period was 5.0 ± 2.2 years. The refractive errors (spherical equivalent) in both eyes were measured preoperatively and postoperatively. Binocular visual function was evaluated with a modified Worth-4 dot test. Results: At the final visit, average anisometropia was 0.98 ± 1.30 D, which was significantly greater than the preoperative value of 0.36 ± 0.46 D ( P < 0.001). Anisometropia ≥2 D was observed in ten patients (23%) postoperatively. One patient was able to fuse a target of ≥2° (10%) in the anisometropia ≥2 D group, significantly fewer than the 13 patients (32%) in the anisometropia <2.0 D group ( P = 0.02). Conclusions: Anisometropia may develop in patients with poor sensory fusion after surgery for esotropia. [ABSTRACT FROM AUTHOR]

It is widely believed that sensory and motor processing in the brain is based on simple computational primitives rooted in cellular and synaptic physiology. However, many gaps remain in our understand- ing of the connections between neural computations and biophysical properties of neurons. Here, we show that synaptic spike-time- dependent plasticity (STDP) combined with spike-frequency adaptation (SFA) in a single neuron together approximate the well-known perceptron learning rule. Our calculations and integrate-and-fire simulations reveal that delayed inputs to a neuron endowed with STDP and SFA precisely instruct neural responses to earlier arriving inputs. We demonstrate this mechanism on a developmental example of auditory map formation guided by visual inputs, as observed in the external nucleus of the inferior colliculus (ICX) of barn owls. The interplay of SFA and STDP in model ICX neurons precisely transfers the tuning curve from the visual modality onto the auditory modality, demonstrating a useful computation for multimodal and sensory- guided processing. [ABSTRACT FROM AUTHOR]

The most common functional benefits from strabismus surgery in the adult patient are restoration of binocular vision and elimination of diplopia and/or a compensatory head posture. Adult patients with chronic strabismus have been thought to have the potential to achieve only a cosmetic result from surgery. On the contrary, several studies have shown that unexpected sensory fusion is possible after excellent postoperative motor alignment in these patients. Other functional benefits of strabismus surgery in the adult patient include the expansion of binocular visual fields in patients with esotropia and the psychosocial and economic benefits from restoration of ocular alignment. This paper will explore the impact of untreated strabismus in the adult patient and what changes occur in the patient's quality of life once strabismus has been successfully treated. [ABSTRACT FROM AUTHOR]

Upright stance was perturbed using sinusoidal platform rotations to see how vestibular and somatosensory information are used to control segment and intersegmental dynamics in subjects with bilateral vestibular loss (BVL) and healthy controls (C). Subjects stood with eyes closed on a rotating platform (±1.2° for frequencies ranging from 0.01–0.4 Hz in the presence and absence of light fingertip touch. Trunk movement relative to the platform of BVLs was higher than Cs at higher platform frequencies whereas leg movement relative to the platform was similar for both groups. With the addition of light touch, both groups showed similar trunk and leg segment movement relative to the platform. Trunk-leg coordination was in-phase for frequencies below 1 Hz and anti-phase above 1 Hz. Interestingly, BVLs showed evidence of a "legs-leading-trunk" relationship in the shift from in-phase to anti-phase around 1 Hz. Controls showed no preference for either segment to lead the coordinative shift from in- to anti-phase. The results suggest that the balance instability of BVL subjects stems from high variability of the trunk, rather than the legs. The high trunk variability may emerge from the "legs-leading" intersegmental relationship upon which BVLs rely. Because BVLs derive information about self-orientation primarily from the support surface when their eyes are closed, the legs initiate the shift to anti-phase trunk-leg coordination that is necessary for stable upright stance control. Higher trunk variability suggests that this strategy results in lower overall postural stability. Light touch substitutes for vestibular information, leading to lower trunk variability along with a trunk-leg phase shift similar to controls, without a preference for either segment to lead the shift. The results suggest that vestibulospinal control acts primarily to stabilize the trunk in space and to facilitate intersegmental dynamics. [ABSTRACT FROM AUTHOR]

Abstract: Saccadic reaction times can be shortened by an additional sensory modality (e.g. auditory, tactile) presented in temporal proximity to the triggering cue. Whereas somatosensory cues given by sudden perturbations of the support surface can trigger appropriate postural adjustments to maintain upright stance, it is not known how gaze executions are affected by the dual task of maintaining upright balance while redirecting gaze. It was hypothesized that the onset latency of gaze movements toward visual targets will be shortened by sudden surface perturbations following visual target shifts to prompt a stable visual anchor for postural stabilization. Eight subjects stood on a movable platform with gaze fixated on a central target 2 m directly in front, and were instructed to shift their gaze to lateral targets located along a 63° arc to the right and left. The trials began with the central target lit followed randomly by either the right, left or center target. Fifty or 250 ms following this target shift, balance was perturbed by a sudden yaw movement of the support surface (15.5° over 210 ms at 130°/s), with no stepping or large arm reactions observed. The latency of the gaze shifts was significantly shortened (by ∼72 ms) when executed simultaneously with a surface perturbation. A decrease in excitation latency was also observed in the cervical paraspinals and sternocleidomastoid muscles. Postural responses in the ankle and knee muscles were not affected by gaze shifts. Pelvic horizontal angular motion closely followed surface motion whereas head motion was influenced by gaze shifts. During the combined gaze shift and surface motion conditions, thorax movement excursion was larger and not correlated with either the surface motion or visual target shift. In conclusion, postural adjustments in response to sudden surface yaws facilitate voluntary gaze shift execution and this enhancement may result from the sensory fusion of somatosensory and visual information. [Copyright &y& Elsevier]

The design and development of conventional controllers for robot platforms are sometimes too complex to achieve due to the fact that they require an exact model of the system and of the operating environment. The ability to pre-account for unknown operating environments is an important task for the controller to be robust. In contrast, biological controllers are model free and are based on simple working principles. Due to natural biological principles these controllers are adaptive and more robust than their conventional counterparts. In this paper, a behaviour-based controller has been developed, inspired by the concept of spinal fields found in frogs and rats. The performance of the controller has been verified on a Khepera robot platform. [ABSTRACT FROM AUTHOR]

The perception of angular displacement during self turning is generally based on a combination of redundant signals from different sources. For example, during active turning in a visually structured environment devoid of landmarks, podokinesthetic, vestibular, and optokinetic velocity signals are fused and integrated over time to yield a unitary percept of the ongoing change in angular position (‘podokinesthetic’ refers to proprioceptive and corollary signals related to leg and foot movement). Previously we have shown that the fusion of two of these afferents improves perceptual accuracy and reliability in comparison to when only one is available. For example, with only a single modality available, slow rotations are perceived to be significantly larger than fast ones, whereas the combination of two modalities greatly reduces this difference. These observations spurred the hypothesis that displacement perception results from a weighted average of bottom-up (sensory) signals and top-down signals (a priori knowledge or expectation), with the weight of the latter decreasing the more sensory information is available. We now ask (1) whether the accuracy of angular displacement estimation can be further improved if it can draw on all three sensory modalities instead of only two, and (2) whether bottom-up sensory and top-down a priori information is combined for displacement estimation in a statistically optimal way. To this end 12 healthy subjects (Ss) standing on a turning platform surrounded by a rotatable optokinetic pattern were exposed to 6 different sensory conditions: pure podokinesthetic (P), vestibular (V), or optokinetic (O) stimulation, and combined podokinesthetic-vestibular (PV), vestibular-optokinetic (VO), or podokinesthetic-vestibular-optokinetic (PVO) stimulation. Stimuli had constant angular velocities of either 15, 30, or 60°/s. Subjects were to press a signal button when they felt that angular displacement had reached a previously instructed magnitude (150–900°). In agreement with earlier observations, the combination of two sensory signals improved the accuracy of displacement perception by reducing both the variance of subjects’ displacement estimates and their dependence on turning velocity. Adding a third sensory signal (condition PVO) led to a further reduction of variance and almost eliminated the effect of velocity. We show that these experimental results are compatible with a probabilistic fusion mechanism based on Bayes’ law. This mechanism would operate on logarithmic representations of turning velocity and proceed in two stages. A first stage fuses all available bottom-up information to create a unitary representation of the velocity signalled by the different sensory modalities. A second stage then fuses this sensory information with top-down a priori information; the latter creates a bias in favour of a ‘default velocity’ that grows as the uncertainty of the sensory information increases. Our experimental data agree with the relation between (1) the variance of displacement estimates and (2) their modulation by velocity predicted by this scheme. [ABSTRACT FROM AUTHOR]

Abstract: Stabilizing the visual system is a crucial issue for any sighted mobile creature, whether it will be natural or artificial. The more immune the gaze of an animal or a robot is to various kinds of disturbances (e.g., those created by body or head movements when walking or flying), the less troublesome it will be for the visual system to carry out its many information processing tasks. The gaze control system that we describe in this paper takes a lesson from the Vestibulo-Ocular Reflex (VOR), which is known to contribute to stabilizing the human gaze and keeping the retinal image steady. The gaze control system owes its originality and its high performances to the combination of two sensory modalities, as follows: [•] a visual sensor called Optical Sensor for the Control of Autonomous Robots (OSCAR) which delivers a retinal angular position signal. A new, miniature (10g), piezo-based version of this visual sensor is presented here; [•] an inertial sensor which delivers an angular head velocity signal. We built a miniature (30g), one degree of freedom oculomotor mechanism equipped with a micro-rate gyro and the new version of the OSCAR visual sensor. The gaze controller involves a feedback control system based on the retinal position error measurement and a feedforward control system based on the angular head velocity measurement. The feedforward control system triggers a high-speed “Vestibulo-ocular reflex” that efficiently and rapidly compensates for any rotational disturbances of the head. We show that a fast rotational step perturbation (3° in 40ms) applied to the head is almost completely (≅90%) rejected within a very short time (70ms). Sinusoidal head perturbations are also rapidly compensated for, thus keeping the gaze stabilized on its target (an edge) within a 10 times smaller angular range than the perturbing head rotations, which were applied here at frequencies of up to 6Hz in an amplitude range of up to 6°. This high standard of performance in terms of head rotational disturbance rejection is comparable to that afforded by the human vestibulo-oculomotor system. [Copyright &y& Elsevier]

Following facial or head trauma, a few unfortunate individuals lose the ability to fuse. With time or treatment, some regain this ability; others have permanent loss of fusion. The fusional mechanism comprises both sensory and motor components with motor fusion being synonymous with the vergence system. If the vergence mechanism is damaged, motor fusion is affected. Although it may he possible to su-perimpose images, they are not maintained together over a range. If sensory fusion is disrupted centrally, superimposition of images is unlikely. Central fusion loss is rare, and almost always follows a head injury. A careful history about the injury may contribute to the differential diagnosis. Convergence paralysis is the most common vergence disorder following head injury. [ABSTRACT FROM AUTHOR]

We ask how vestibular and optokinetic information is combined ("fused") when human subjects who are being passively rotated while viewing a stationary optokinetic pattern try to tell when they have reached a previously instructed angular displacement ("targeting task"). Inevitably such a task entices subjects to also draw on cognitive mechanisms such as past experience and contextual expectations. Specifically, because we used rotations of constant angular velocity, we suspected that they would resort, consciously or unconsciously, to extrapolation strategies even though they had no explicit knowledge of this fact. To study these issues, we presented the following six conditions to subjects standing on a rotatable platform inside an optokinetic drum: V, pure vestibular (passive rotation in darkness); O, pure optokinetic (observer motionless, drum rotating); VO, combined (passive rotation while viewing stationary drum); Oe, optokinetic extrapolation (similar to O, but drum visible only during first 90° of rotation; thereafter subjects extrapolate the further course in their minds); VOe, combined extrapolation (similar to VO, but drum visible only during first 90°); AI, auditory imagination (rotation presented only metaphorically; observers imagine a drum rotation using the rising pitch of a tone as cue). In all conditions, angular velocities (vC) of 15, 30, or 60°/s were used (randomized presentation), and observers were to indicate when angular displacement (of the self in space or relative to the drum) had reached the instructed magnitude ("desired displacement", DD; range 90–900°). Performance was analyzed in terms of the targeting gain (GT = physical displacement at time of subjects' indication / DD) and variability (%ER = percentage absolute deviation from a subject's mean gain). In all six conditions, the global mean of GT (across vC and DD) was remarkably close to veracity, ranging from 0.95 (V) to 1.06 (O). A more detailed analysis of the gain revealed a trend of GT to be larger with fast than with slow rotations, reflecting an underestimation of fast and an overestimation of slow rotation. This effect varied significantly between conditions: it was smallest in VO, had intermediate values with the monomodal conditions V and O, and also with VOe, and was largest in Oe and AI. Variability was similar for all velocities, but depended significantly on the condition: it was smallest in VO, of intermediate magnitude in O, VOe, Oe, and largest in V and AI. Additional experiments with conditions V, O, and VO in which subjects repetitively indicated displacement increments of 90°, up to a subjective displacement of 1080°, yielded similar results and suggest, in addition, that the displacement perceptions measured at the beginning and during later phases of the rotation are correlated. With respect to the displacement perception during optokinetic stimulation, they also show that the gain and its variability are similar whether subjects feel stationary and see a rotating pattern, or feel rotated and see a stationary pattern (circular vection). We conclude that the vestibular and optokinetic information guiding the subjects' navigation toward an instructed target is not fused by straightforward averaging. Rather the subjects' internal velocity representation (which ultimately determines GT) appears to be a weighted average of (1) whatever sensory information is available and of (2) a cognitive default value reflecting the subjects' experiences and expectations. The less secure the sensory information (only one source as in V or O, additional degrading as in Oe or AI), the larger the weight of the default value. Vice versa, the better the information (e.g., two independent sources as in VO), the more the actual velocity and not the default value determines displacement perception. Moreover, we suggest that subjects intuitively proceeded from the notion of a constant velocity rotation, and therefore tended to carry on the perception built up during the beginning of a rotation or, in the case of vestibular navigation, to compensate for the decaying vestibular cue by means of an internal recovery mechanism. [ABSTRACT FROM AUTHOR]

This paper provides an extensive experimental and analytical evaluation of a previously presented approach to the systematic design of condition monitoring systems for machining operations [J. Mater. Process. Technol. 107 (2000) 243]. The methodology termed automated sensor and signal processing selection (ASPS), is based on Taguchi’s orthogonal arrays in order to provide cost effective and speedy selection of sensors and signal processing methods that are ultimately used for monitoring process conditions. The evaluation using tool damage in end milling operations shows that ASPS methodology can successfully achieve its objectives without significantly affecting the system’s capability for fault detection. The experiments investigate two new types of cutting tools each with three distinct conditions which are processed by four different and independent neural network paradigms—two supervised and two unsupervised. Thus, the results confirm the feasibility and efficiency of the proposed ASPS methodology and show that it can be applied to condition monitoring systems without the need for implementing pattern recognition tools during the design phase. [Copyright &y& Elsevier]

When observers step about their vertical axis ("active turning") without vision they dispose of essentially two sources of information that can tell them by how much they have turned: the vestibular cue which reflects head rotation in space and the "podokinesthetic" cue, a compound of leg proprioceptive afferents and efference copy signals which reflects the observer's motion relative to his support. We ask how these two cues are fused in the process leading to the perception of self-displacement during active turning. To this end we compared the performance of observers in three angular navigation tasks which differed with regard to the number and type of available motion cues: (1) Passive rotation, vestibular cue (ves) only; observers are standing on a platform which is being rotated. (2) Treadmill stepping, podokinesthetic cue (pod) only; observers step counter to the rotating platform so as to remain stable in space. (3) Active turning, ves and pod available; observers step around on the stationary platform. In all three tasks, angular velocity varied from trial to trial (15, 30, 60°/s) but was constant during trials. Perception was probed by having the observers signal when they thought to have reached a previously instructed angular displacement, either in space or relative to the platform ("target"; range 60–1080°). Performance was quantified in terms of the targeting gain (displacement reached by the observer divided by target angle) and of the random error (Er), which records an observer's deviation during single trials from his average performance. Confirming previous observations, Er was found to be significantly smaller during active turning than during passive turning, and we now complement these observations by showing that it is also significantly smaller than during treadmill stepping. This behaviour of Er is compatible with the idea that ves and pod be averaged during active turning. On the other hand, the observed characteristics of the targeting gain (GT) support this idea only for the case of fast rotations (60°/s); at lower velocities, the gain found during active turning was clearly not the average of the GT values recorded in the passive and the treadmill modes. We therefore also discuss alternative scenarios as to how ves and pod could interact, among these one based on the concept of a vestibular eigenmodel. A common denominator of these scenarios is that ves assumes the role of a prerequisite for an optimal use of pod during turning on a stationary support, without itself entering the calculation of displacement perception; this perception would be based exclusively on pod. Finally, it was a consistent observation that during passive rotations cognitive mechanisms fill in for the decaying vestibular signal in the context of the present navigation task, enabling observers to achieve large displacements surprisingly well although the duration of these movements exceeds by far the conventionally cited value of the central vestibular time constant (=20 s). [ABSTRACT FROM AUTHOR]

Despite extensive research on the influence of visual, vestibular and somatosensory information on human postural control, it remains unclear how these sensory channels are fused for self-orientation. The focus of the present study was to test whether a linear additive model could account for the fusion of touch and vision for postural control. We simultaneously manipulated visual and somatosensory (touch) stimuli in five conditions of single- and multisensory stimulation. The visual stimulus was a display of random dots projected onto a screen in front of the standing subject. The somatosensory stimulus was a rigid plate which subjects contacted lightly (<1 N of force) with their right index fingertip. In each condition, one sensory stimulus oscillated (dynamic) in the medial-lateral direction while the other stimulus was either dynamic, static or absent. The results qualitatively supported five predictions of the linear additive model in that the patterns of gain and variability across conditions were consistent with model predictions. However, a strict quantitative comparison revealed significant deviations from model predictions, indicating that the sensory fusion process clearly has nonlinear aspects. We suggest that the sensory fusion process behaved in an approximately linear fashion because the experimental paradigm tested postural control very close to the equilibrium point of vertical upright. [ABSTRACT FROM AUTHOR]

The present work compares passive and active rotations in darkness with the aim of characterizing the contribution of efferent and proprioceptive information to the perception of angular displacement. The perception of angular displacements was measured in 12 naive subjects (Ss), who either stood on a rotating platform (passive mode, P) or actively turned about their vertical axis by stepping around ”on the spot” on a stationary platform (active mode, A). Rotations consisted of short acceleration epochs followed by constant velocity periods of 18.5, 37, and 55°/s, with angular displacements ranging from 30° to 810° (presented in a randomized order); in the case of active turning, Ss had learned to approximately produce any of these three velocity levels on command. Ss indicated perceived displacement either verbally (verbal estimation mode, E), or by stopping their rotation when self-displacement appeared to match the magnitude specified by the experimenter (targeting, T). The resulting four conditions (PE, PT, AE, AT) were administered blockwise. In none of the four conditions was there a systematic dependence of perception on turning velocity. Therefore, the results were pooled across velocities, and the Ss’ performance was summarized in the form of estimation curves showing median estimates as a function of physical displacement. There were several differences between the passive and active modes: AE- and AT-estimation curves were linear, close to veracity, and fairly similar to each other. In contrast, the PE-curve was curved rightwardly (”saturation”), with small displacements being overestimated and large ones underestimated, whereas the PT-curve was linear and indicated a pronounced overestimation of large displacements. Moreover, both the random and the systematic errors (measures of individual consistency and correctness of individual calibration, respectively) were significantly smaller in the active than in the passive modes. The observed independence of Ss’ perception from turning velocity also during passive rotation suggests that the perceptual time constant was significantly longer than 16 s (a value cited as typical for vestibular perception), being possibly ”enhanced” by contextual implications and by expectations of the Ss. The clear improvement of perceptual performance in the active mode testifies to the importance of the efferent and proprioceptive signals arising during active motion. On the assumption that these signals are about as ”noisy” as the vestibular ones, the smaller errors during active turning could result from their combination with the vestibular signal. Alternatively, they could also be intrinsically less noisy than the vestibular signal and simply replace the latter during active motion. In the context of these alternatives (which are not exhaustive), the general problem of sensory fusion is discussed, that is, by which mechanisms are signals from different sensory sources combined to obtain a unified representation of the self’s orientation. [ABSTRACT FROM AUTHOR]

One of the biggest challenges of any control paradigm is being able to handle large complex systems. A system may be called large-scale or complex, here, if its dimension (order) is so high and its model (if available) is nonlinear, interconnected with uncertain information flow such that classical techniques of control theory cannot easily handle the system. From a control theoretical point of view, fuzzy logic has been intermixed with all the important aspects of systems theory - modeling, identification, analysis, stability, synthesis, filtering, and estimation. However, the application of fuzzy control to large-scale complex systems is not a trivial task by any means. For such systems the size of the rule base in a typical fuzzy control architecture will be nearly infinite. In this paper an attempt is made to break some new ground on the applications of fuzzy control to complex systems. A new rule base reduction approach is suggested to manage large inference engines. Notions of rule hierarchy and sensor data fusion are introduced and combined to achieve system’s goals. The technique has been implemented on an SGS Thomson W.A.R.P. chip for an inverted pendulum with wine-balancing application. [ABSTRACT FROM AUTHOR]

When combining information across different senses, humans need to flexibly select cues of a common origin while avoiding distraction from irrelevant inputs. The brain could solve this challenge using a hierarchical principle by deriving rapidly a fused sensory estimate for computational expediency and, later and if required, filtering out irrelevant signals based on the inferred sensory cause(s). Analyzing time- and source-resolved human magnetoencephalographic data, we unveil a systematic spatiotemporal cascade of the relevant computations, starting with early segregated unisensory representations, continuing with sensory fusion in parietal-temporal regions, and culminating as causal inference in the frontal lobe. Our results reconcile previous computational accounts of multisensory perception by showing that prefrontal cortex guides flexible integrative behavior based on candidate representations established in sensory and association cortices, thereby framing multisensory integration in the generalized context of adaptive behavior. • Flexible use of multisensory information follows Bayesian inference • Sensory fusion emerges earlier than causal inference • Multisensory inference is represented in the frontal lobe • Inferior frontal regions guide perception in discrepant environments Humans combine multisensory information sharing a common cause while avoiding distraction from irrelevant sources. Cao et al. show how this flexible sensory inference is guided by prefrontal cortex and unfolds as sequential neural computations comprising functionally distinct multisensory representations. [ABSTRACT FROM AUTHOR]