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With the advent of robotics and artificial intelligence, the potential for automating tasks within human-centric environments has increased significantly. This is particularly relevant in the retail sector where the demand for efficient operations and the shortage of labor drive the need for rapid advancements in robot-based technologies. Densely packed retail shelves pose unique challenges for robotic manipulation and detection due to limited space and diverse object shapes. Vacuum-based grasping technologies offer a promising solution but face challenges with object shape adaptability. The study proposes a framework for robotic grasping in retail environments, an adaptive vacuum-based grasping solution, and a new evaluation metric-termed grasp shear force resilience-for measuring the effectiveness and stability of the grasp during manipulation. The metric provides insights into how retail objects behave under different manipulation scenarios, allowing for better assessment and optimization of robotic grasping performance. The study's findings demonstrate the adaptive suction cups' ability to successfully handle a wide range of object shapes and sizes, which, in some cases, overcome commercially available solutions, particularly in adaptability. Additionally, the grasp shear force resilience metric highlights the effects of the manipulation process, such as in shear force and shake, on the manipulated object. This offers insights into its interaction with different vacuum cup grasping solutions in retail picking and restocking scenarios.

This paper explores the possibility of distributing the fields of view (FOVs) of a centralized lidar cluster using fixed mirrors for future use in safety applications in robotics and elsewhere. A custom modular lidar system with time-over-threshold (TOT) walk error compensation was developed for the experiments. It comprises a control board that provides the processing power and adjustable voltage regulation, and multiple individually addressable analogue front end (AFE) boards that each contain a transmitter, a receiver, time-to-digital (TDC) converters for pulse width measurements on the bot Tx and Rx side, and adjustable reference voltage generators for both the Tx and Rx pulse detection threshold. The lidar system's performance with a target in the direct line of sight is compared to the configurations where the FOV is redirected with up to three mirrors in different configurations. The results show that the light path through the neighboring mirrors introduces a minor but noticeable measurement error on a portion of the measurement range.

Patients after stroke need to re-learn functional movements required for independent living throughout the rehabilitation process. In the study, we used a wearable sensory system for monitoring the movement of the upper limbs while performing activities of daily living. We implemented time-based and path-based segmentation of movement trajectories and muscle activity to quantify the activities of the unaffected and the affected upper limbs. While time-based segmentation splits the trajectory in quants of equal duration, path-based segmentation isolates completed movements. We analyzed the hand movement path and forearm muscle activity and introduced a bimanual movement parameter, which enables differentiation between unimanual and bimanual activities. The approach was validated in a study that included a healthy subject and seven patients after stroke with different levels of disabilities. Path-based segmentation provides a more detailed and comprehensive evaluation of upper limb activities, while time-based segmentation is more suitable for real-time assessment and providing feedback to patients. Bimanual movement parameter effectively differentiates between different levels of upper limb involvement and is a clear indicator of the activity of the affected limb relative to the unaffected limb.

This study focuses on the feasibility of collaborative robot implementation in a medical microbiology laboratory by demonstrating fine tasks using kinesthetic teaching. Fine tasks require sub-millimetre positioning accuracy. Bacterial colony picking and identification was used as a case study. Colonies were picked from Petri dishes and identified using matrix-assisted laser desorption/ionization (MALDI) time-of-flight (TOF) mass spectrometry. We picked and identified 56 colonies (36 colonies of Gram-negative Acinetobacter baumannii and 20 colonies of Gram-positive Staphylococcus epidermidis ). The overall identification error rate was around 11%, although it was significantly lower for Gram-positive bacteria (5%) than Gram-negative bacteria (13.9%). Based on the identification scores, it was concluded that the system works similarly well as a manual operator. It was determined that tasks were successfully demonstrated using kinesthetic teaching and generalized using dynamic movement primitives (DMP). Further improvement of the identification error rate is possible by choosing a different deposited sample treatment method (e.g., semi-extraction, wet deposition).

An ultra-wideband (UWB) localization system is an alternative in a GPS-denied environment. However, a distance measurement with UWB modules using a two-way communication protocol induces an orientation-dependent error. Previous research studied this error by looking at parameters such as the received power and the channel response signal. In this paper, the neural network (NN) method for correcting the orientation-induced distance error without the need to calculate the signal strength, obtain the channel response or know any parameters of the antenna and the UWB modules is presented. The NN method utilizes only the measured distance and the tag orientation, and implements an NN model obtained by machine learning, using measurements at different distances and orientations of the two UWB modules. The verification of the experimental setup with 12 anchors and a tag shows that with the proposed NN method, 5 cm better root mean square error values (RMSEs) are obtained for the measured distance between the anchors and the tag compared to the calibration method that did not include orientation information. With the least-square estimator, 14 cm RMSE in 3D is obtained with the NN model corrected distances, with a 9 cm improvement compared to when raw distances are used. The method produces better results without the need to obtain the UWB module's diagnostics parameters that are required to calculate the received signal strength or channel response, and in this way maintain the minimum packet size for the ranging protocol.

Estimation of the centre of pressure (COP) is an important part of the gait analysis, for example, when evaluating the functional capacity of individuals affected by motor impairment. Inertial measurement units (IMUs) and force sensors are commonly used to measure gait characteristic of healthy and impaired subjects. We present a methodology for estimating the COP solely from raw gyroscope, accelerometer, and magnetometer data from IMUs using statistical modelling. We demonstrate the viability of the method using an example of two models: a linear model and a non-linear Long-Short-Term Memory (LSTM) neural network model. Models were trained on the COP ground truth data measured using an instrumented treadmill and achieved the average intra-subject root mean square (RMS) error between estimated and ground truth COP of 12.3 mm and the average inter-subject RMS error of 23.7 mm which is comparable or better than similar studies so far. We show that the calibration procedure in the instrumented treadmill can be as short as a couple of minutes without the decrease in our model performance. We also show that the magnetic component of the recorded IMU signal, which is most sensitive to environmental changes, can be safely dropped without a significant decrease in model performance. Finally, we show that the number of IMUs can be reduced to five without deterioration in the model performance.

Wearable robotic devices require sensors and algorithms that can recognize the user state in real-time, in order to provide synergistic action with the body. For devices intended for locomotion-related applications, shoe-embedded sensors are a common and convenient choice, potentially advantageous for performing gait assessment in real-world environments. In this work, we present the development of a pair of pressure-sensitive insoles based on optoelectronic sensors for the real-time estimation of temporal gait parameters. The new design makes use of a simplified sensor configuration that preserves the time accuracy of gait event detection relative to previous prototypes. The system has been assessed relatively to a commercial force plate recording the vertical component of the ground reaction force (vGRF) and the coordinate of the center of pressure along the so-called progression or antero-posterior plane (CoP AP ) in ten healthy participants during ground-level walking at two speeds. The insoles showed overall median absolute errors (MAE) of 0.06 (0.02) s and 0.04 (0.02) s for heel-strike and toe-off recognition, respectively. Moreover, they enabled reasonably accurate estimations of the stance phase duration (2.02 (2.03) % error) and CoP AP profiles (Pearson correlation coefficient with force platform ρCoP = 0.96 (0.02)), whereas the correlation with vGRF measured by the force plate was lower than that obtained with the previous prototype (ρvGRF = 0.47 (0.20)). These results confirm the suitability of the insoles for online sensing purposes such as timely gait phase estimation and discrete event recognition.

Infant posture and motor pattern development are normally analyzed by clinical assessment scales. Lately, this approach is combined with the use of sensor-supported systems, such as optical, inertial, and electromagnetic measurement systems, as well as novel assessment devices, such as CareToy. CareToy is a modular device for assessment and rehabilitation of preterm infants, comprising pressure mattresses, inertial and magnetic measurement units, and sensorized toys. Since such integrated sensor system combination is new to the field of sensor-supported infant behavior assessment and rehabilitation, dedicated methods for data analysis were developed and presented. These comprise trunk rotation, arm movement, forearm orientation, and head movement analysis, along with toy play and trunk posture stability evaluation. Methods were tested on case study data, evaluating suitability of developed algorithms for infant posture and activity analysis, regardless of behavioral responses. Obtained results demonstrate suitability of the proposed methods for successful use in studies of different motor pattern subfields. This represents an important step on the course towards objective, accurate, sensor-supported infant motor development assessment. Graphical abstract Posture and movement assessment of infants using analysis of sensory data, obtained with a dedicated sensorized gym with toys.

The CYBERLEGs Beta-Prosthesis is an active transfemoral prosthesis that can provide the full torque required for reproducing average level ground walking at both the knee and ankle in the sagittal plane. The prosthesis attempts to produce a natural level ground walking gait that approximates the joint torques and kinematics of a non-amputee while maintaining passively compliant joints, the stiffnesses of which were derived from biological quasi-stiffness measurements. The ankle of the prosthesis consists of a series elastic actuator with a parallel spring and the knee is composed of three different systems that must compliment each other to generate the correct joint behavior: a series elastic actuator, a lockable parallel spring and an energy transfer mechanism. Bench testing of this new prosthesis was completed and demonstrated that the device was able to create the expected torque-angle characteristics for a normal walker under ideal conditions. The experimental trials with four amputees walking on a treadmill to validate the behavior of the prosthesis proved that although the prosthesis could be controlled in a way that allowed all subjects to walk, the accurate timing and kinematic requirements of the output of the device limited the efficacy of using springs with quasi-static stiffnesses. Modification of the control and stiffness of the series springs could provide better performance in future work.

In patients after stroke, ability of the upper limb is commonly assessed with standardised clinical tests that provide a complete upper limb assessment. This paper presents quantification of upper limb movement during the execution of Action research arm test (ARAT) using a wearable system of inertial measurement units (IMU) for kinematic quantification and electromyography (EMG) sensors for muscle activity analysis. The test was executed with each arm by a group of healthy subjects and a group of patients after stroke allocated into subgroups based on their clinical scores. Tasks were segmented into movement and manipulation phases. Each movement phase was quantified with a set of five parameters: movement time, movement smoothness, hand trajectory similarity, trunk stability, and muscle activity for grasping. Parameters vary between subject groups, between tasks, and between task phases. Statistically significant differences were observed between patient groups that obtained different clinical scores, between healthy subjects and patients, and between the unaffected and the affected arm unless the affected arm shows normal performance. Movement quantification enables differentiation between different subject groups within movement phases as well as for the complete task. Spearman's rank correlation coefficient shows strong correlations between patient's ARAT scores and movement time as well as movement smoothness. Weak to moderate correlations were observed for parameters that describe hand trajectory similarity and trunk stability. Muscle activity correlates well with grasping activity and the level of grasping force in all groups.

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 , ) 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.

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.

An emerging approach to design locomotion assistive devices deals with reproducing desirable biological principles of human locomotion. In this paper, we present a bio-inspired controller for locomotion assistive devices based on the concept of motor primitives. The weighted combination of artificial primitives results in a set of virtual muscle stimulations. These stimulations then activate a virtual musculoskeletal model producing reference assistive torque profiles for different locomotion tasks (i.e., walking, ascending stairs, and descending stairs). The paper reports the validation of the controller through a set of experiments conducted with healthy participants. The proposed controller was tested for the first time with a unilateral leg exoskeleton assisting hip, knee, and ankle joints by delivering a fraction of the computed reference torques. Importantly, subjects performed a track involving ground-level walking, ascending stairs, and descending stairs and several transitions between these tasks. These experiments highlighted the capability of the controller to provide relevant assistive torques and to effectively handle transitions between the tasks. Subjects displayed a natural interaction with the device. Moreover, they significantly decreased the time needed to complete the track when the assistance was provided, as compared to wearing the device with no assistance.

Early intervention programs aim at improving cognitive and motor outcomes of preterm infants. Intensive custom-tailored training activities are usually accompanied by assessment procedures, which have shortcomings, such as subjectivity, complex setups, and need for structured environments. A novel sensorized system, called CareToy, was designed to provide stimulation in the form of goal-directed activity training scenarios and motor pattern assessment of main developmental milestones, such as rolling activity, grasping, and postural stability. A group of 28 differently skilled preterm infants were enrolled. Acquired measurement data were analysed with dedicated sensor data processing algorithms, along with clinical evaluation of motor ability. High correlation among technically determined parameters and Alberta Infant Motor Scale values was determined by Pearson correlation coefficients. Due to good accuracy and possibility of single motor skill subfield analysis, results confirm system suitability for motor ability assessment. Statistical analysis of inter-motor ability group and inter-training goal data comparisons demonstrate system's appropriateness for goal-directed activity stimulation. The proposed system has evident potential of being an important contribution to the field of infant motor development assessment, expanding accessibility of early intervention programs and affecting rehabilitation effectiveness of preterm infants.

This study uses inertial sensors to measure ski jumper kinematics and joint dynamics, which was until now only a part of simulation studies. For subsequent calculation of dynamics in the joints, a link-segment model was developed. The model relies on the recursive Newton-Euler inverse dynamics. This approach allowed the calculation of the ground reaction force at take-off. For the model validation, four ski jumpers from the National Nordic center performed a simulated jump in a laboratory environment on a force platform; in total, 20 jumps were recorded. The results fit well to the reference system, presenting small errors in the mean and standard deviation and small root-mean-square errors. The error is under 12% of the reference value. For field tests, six jumpers participated in the study; in total, 28 jumps were recorded. All of the measured forces and moments were within the range of prior simulated studies. The proposed system was able to indirectly provide the values of forces and moments in the joints of the ski-jumpers' body segments, as well as the ground reaction force during the in-run and take-off phases in comparison to the force platform installed on the table. Kinematics assessment and estimation of dynamics parameters can be applied to jumps from any ski jumping hill.

Head movement of infants is an important parameter for analysing infant motor patterns. Despite its importance, this field has received little sensory-based research in the past years. Therefore, we present a sensory-supported data fusion model for head movement analysis of infants in supine position. The sensory system comprises a pressure mattress and two wireless inertial magnetic measurement units, rendering precise, objective and non-intrusive information on pressure distribution and 3D trunk orientation, respectively. Algorithms first perform pressure data pre-processing and calculate image moments to acquire 2D trunk orientation. Afterwards, unscented Kalman filter is used for sensory data fusion. After additional data processing, head and trunk coordinates are calculated along with head displacement distance. The sensory system was tested on experimental measurements, performed in eight normally developing infants aged from 1 to 5 months. Results of several algorithm combinations were compared to referential video recordings in terms of head lifts. Combination of algorithms, incorporating head tracking and sensory data fusion provides completely accurate results in comparison to normative data. Statistical data analysis and referential optoelectronic measurements were performed to evaluate accuracy of the sensory fusion model. Suitability of the proposed sensory system for head movement analysis of infants in supine position was verified.

In this paper, we present a fuzzy-logic-based hybrid locomotion mode classification method for an active pelvis orthosis. Locomotion information measured by the onboard hip joint angle sensors and the pressure insoles is used to classify five locomotion modes, including two static modes (sitting, standing still), and three dynamic modes (level-ground walking, ascending stairs, and descending stairs). The proposed method classifies these two kinds of modes first by monitoring the variation of the relative hip joint angle between the two legs within a specific period. Static states are then classified by the time-based absolute hip joint angle. As for dynamic modes, a fuzzy-logic based method is proposed for the classification. Preliminary experimental results with three able-bodied subjects achieve an off-line classification accuracy higher than 99.49%.

Previous studies have presented algorithms for detection of turns during gait using wearable sensors, but those algorithms were not built for real-time use. This paper therefore investigates the optimal approach for real-time detection of planned turns during gait using wearable inertial measurement units. Several different sensor positions (head, back and legs) and three different detection criteria (orientation, angular velocity and both) are compared with regard to their ability to correctly detect turn onset. Furthermore, the different sensor positions are compared with regard to their ability to predict the turn direction and amplitude. The evaluation was performed on ten healthy subjects who performed left/right turns at three amplitudes (22, 45 and 90 degrees). Results showed that turn onset can be most accurately detected with sensors on the back and using a combination of orientation and angular velocity. The same setup also gives the best prediction of turn direction and amplitude. Preliminary measurements with a single amputee were also performed and highlighted important differences such as slower turning that need to be taken into account.

Background: Existing motor pattern assessment methods, such as digital cameras and optoelectronic systems, suffer from object obstruction and require complex setups. To overcome these drawbacks, this paper presents a novel approach for biomechanical evaluation of newborn motor skills development. Multi-sensor measurement system comprising pressure mattress and IMUs fixed on trunk and arms is proposed and used as alternative to existing methods. Observed advantages seem appealing for the focused field and in general. Combined use of pressure distribution data and kinematic information is important also for posture assessment, ulcer prevention, and non-invasive sleep pattern analysis of adults., Methods: Arm kinematic parameters, such as root-mean-square acceleration, spectral arc length of hand velocity profile, including arm workspace surface area, and travelled hand path are obtained with the multi-sensor measurement system and compared to normative motion capture data for evaluation of adequacy. Two IMUs per arm, only one IMU on upper arm, and only one IMU on forearm sensor placement options are studied to assess influence of system configuration on method precision. Combination of pressure mattress and IMU fixed on the trunk is used to measure trunk position (obtained from mat), rotation (from IMUs) and associated movements on surface (from both). Measurement system is first validated on spontaneous arm and trunk movements of a dedicated baby doll having realistic anthropometric characteristics of newborns. Next, parameters of movements in a healthy infant are obtained with pressure mattress, along with trunk and forearm IMU sensors to verify appropriateness of method and parameters., Results: Evaluation results confirm that full sensor set, comprising pressure mattress and two IMUs per arm is a reliable substitution to optoelectronic systems. Motor pattern parameter errors are under 10% and kinematic estimation error is in range of 2 cm. Although, use of only forearm IMU is not providing best possible kinematic precision, the simplicity of use and still acceptable accuracy are convincing for frequent practical use. Measurements demonstrated system high mobility and usability., Conclusions: Study results confirm adequacy of the proposed multi-sensor measurement system, indicating its enviable potential for accurate infant trunk posture and arm movement assessment.

This paper presents a gait phase detection algorithm for providing feedback in walking with a robotic prosthesis. The algorithm utilizes the output signals of a wearable wireless sensory system incorporating sensorized shoe insoles and inertial measurement units attached to body segments. The principle of detecting transitions between gait phases is based on heuristic threshold rules, dividing a steady-state walking stride into four phases. For the evaluation of the algorithm, experiments with three amputees, walking with the robotic prosthesis and wearable sensors, were performed. Results show a high rate of successful detection for all four phases (the average success rate across all subjects >90%). A comparison of the proposed method to an off-line trained algorithm using hidden Markov models reveals a similar performance achieved without the need for learning dataset acquisition and previous model training.

This paper presents algorithms for detection of gait initiation and termination using wearable inertial measurement units and pressure-sensitive insoles. Body joint angles, joint angular velocities, ground reaction force and center of plantar pressure of each foot are obtained from these sensors and input into supervised machine learning algorithms. The proposed initiation detection method recognizes two events: gait onset (an anticipatory movement preceding foot lifting) and toe-off. The termination detection algorithm segments gait into steps, measures the signals over a buffer at the beginning of each step, and determines whether this measurement belongs to the final step. The approach is validated with 10 subjects at two gait speeds, using within-subject and subject-independent cross-validation. Results show that gait initiation can be detected timely and accurately, with few errors in the case of within-subject cross-validation and overall good performance in subject-independent cross-validation. Gait termination can be predicted in over 80% of trials well before the subject comes to a complete stop. Results also show that the two sensor types are equivalent in predicting gait initiation while inertial measurement units are generally superior in predicting gait termination. Potential use of the algorithms is foreseen primarily with assistive devices such as prostheses and exoskeletons., (Copyright © 2013 IPEM. Published by Elsevier Ltd. All rights reserved.)

Current experimental methods for the study of reaching in the MRI environment do not exactly mimic actual reaching, due to constrains in movement which are imposed by the MRI machine itself. We tested a haptic robot (HR) as such a tool. Positive results would also be promising for combined use of fMRI and EEG to study reaching. Twenty right-handed subjects performed reaching tasks with their right hand with and without the HR. Reaction time, movement time (MT), accuracy, event-related potentials (ERPs) and event-related desynchronisation/synchronisation (ERD/ERS) were studied. Reaction times and accuracies did not differ significantly between the two tasks, while the MT was significantly longer in HR reaching (959 vs. 447 ms). We identified two positive and two negative ERP peaks across all leads in both tasks. The latencies of the P1 and N2 peaks were significantly longer in HR reaching, while there were no significant differences in the P3 and N4 latencies. ERD/ERS topographies were similar between tasks and similar to other reaching studies. Main difference was in ERS rebound which was observed only in actual reaching. Probable reason was significantly larger MT. We found that reaching with the HR engages similar neural structures as in actual reaching. Although there are some constrains, its use may be superior to other techniques used for reaching studies in the MRI environment, where freedom of movement is limited.

The aim of this study was to analyse the asymmetry of sit-to-stand (STS) movement in a group of subjects following unilateral transtibial amputation (STTA) and a group of healthy subjects (HSs). Experimental measurements investigated standing-up pattern from two seat heights and at three different speeds. Body motion was measured using an optical measuring system with active markers. Floor and seat reaction forces and moments were measured by two force plates and an integrated force-moment sensor. Analysis of ankle, knee, hip and trunk inclination angles shows that STTA perform STS movement with different initial foot placement than HS, resulting in different lower extremity loadings and larger trunk inclination. Asymmetry was defined as the difference between left and right extremity parameters averaged throughout STS movement. A root-mean-square error was used to assess the asymmetry in ground reaction forces and in ankle, knee and hip angles and moments. The influence of different seat heights and velocities on asymmetry was tested using one-way ANOVA. The asymmetry of STTA and HS was affected neither in kinematic nor in kinetic parameters. Performing STS at higher speeds was found to result in decreased trunk flexion. The asymmetry assessment, as determined in this study, can be used in rehabilitation for improving STS strategies or as an evaluation tool for estimating the progress of the rehabilitation process.

This paper presents an analysis of the rowing parameters of differently skilled rowers. The study focuses on technique dependency on stroke rate. Five elite, five junior and five non-rowers participated, and the biomechanics of rowing on an ergometer was analyzed at stroke rates of 20, 26 and 34 str/min. The results show that elite rowers use a similar, consistent rowing technique at all stroke rates, the technique of junior rowers follows similar principles, while the technique of non-rowers varies. Elite rowers' stroke length, handle motion and body posture do not change with stroke rate while the ratio of stroke phases, maximum forces, stroke work and joint loadings are constant at the same stroke rate but dependent on stroke rate. Junior rowers with stroke rate change also the stroke length. In non-rowers the differences can be observed in the handle motion and body posture during the stroke, their stroke length changes with stroke rate while the ratio of stroke phases stays constant. Although different movement execution is evident and variable with stroke rate, non-rowers demonstrate a consistent pattern at the same stroke rate. On the basis of the results, the crucial parameters that differentiate elite, junior, and non-rowers are identified., (Copyright © 2012 Elsevier B.V. All rights reserved.)

This paper describes a custom, material-type-independent laser-triangulation-based measurement system that utilizes a high-quality ultraviolet laser beam. Laser structuring applications demand material surface alignment regarding the laser focus position, where fabrication conditions are optimal. Robust alignment of various material types was solved by introducing dynamic symmetrical pattern projection, and a "double curve fitting" centroid detection algorithm with subsurface scattering compensation. Experimental results have shown that the measurement system proves robust to laser intensity variation, with measurement bias lower than 50 μm and standard deviation lower than ±6.3 μm for all materials. The developed probe has been integrated into a PCB prototyping system for material referencing purposes.

A diagnostic platform for the early functional assessment of post-stroke patients was designed in order to perform isometric measurements during activities of daily living (ADL) tasks. The outcome of these measurements can contribute to verify the integrity of a post-stroke existing or altered "internal model" for a particular functional task. A complete and reliable software application for the diagnostic platform was designed, developed and tested in three European hospitals. The software application was divided into two main modules: a graphical user interface (GUI) and the data pre-processing techniques for the interpretation of recorded biomedical and clinical data. This paper presents the software application associated to the platform, aimed at analysing and interpreting the huge amount of data recorded and collected during the experimental trials. Its main objective is related to validating the onset detection and data reduction. The software application presented in this paper has been working and validated with success in three different clinical centres in Europe and it can be effectively used both as assessment tool in rehabilitation and as research tool in neuroscience., (Copyright © 2012 Elsevier Ireland Ltd. All rights reserved.)

We present a sensor technology for the measure of the physical human-robot interaction pressure developed in the last years at Scuola Superiore Sant'Anna. The system is composed of flexible matrices of opto-electronic sensors covered by a soft silicone cover. This sensory system is completely modular and scalable, allowing one to cover areas of any sizes and shapes, and to measure different pressure ranges. In this work we present the main application areas for this technology. A first generation of the system was used to monitor human-robot interaction in upper- (NEUROExos; Scuola Superiore Sant'Anna) and lower-limb (LOPES; University of Twente) exoskeletons for rehabilitation. A second generation, with increased resolution and wireless connection, was used to develop a pressure-sensitive foot insole and an improved human-robot interaction measurement systems. The experimental characterization of the latter system along with its validation on three healthy subjects is presented here for the first time. A perspective on future uses and development of the technology is finally drafted.

Background: Humans are capable of fast adaptation to new unknown dynamics that affect their movements. Such motor learning is also believed to be an important part of motor rehabilitation. Bimanual training can improve post-stroke rehabilitation outcome and is associated with interlimb coordination between both limbs. Some studies indicate partial transfer of skills among limbs of healthy individuals. Another aspect of bimanual training is the (a)symmetry of bimanual movements and how these affect motor learning and possibly post-stroke rehabilitation., Methods: A novel bimanual 2-DOF robotic system was used for both bimanual and unimanual reaching movements. 35 young healthy adults participated in the study. They were divided into 5 test groups that performed movements under different conditions (bimanual or unimanual movements and symmetric or asymmetric bimanual arm loads). The subjects performed a simple tracking exercise with the bimanual system. The exercise was developed to stimulate motor learning by applying a velocity-dependent disturbance torque to the handlebar. Each subject performed 255 trials divided into three phases: baseline without disturbance torque, training phase with disturbance torque and evaluation phase with disturbance torque., Results: Performance was assessed with the maximal values of rotation errors of the handlebar. After exposure to disturbance torque, the errors decreased for both unimanual and bimanual training. Errors in unimanual evaluation following the bimanual training phase were not significantly different from errors in unimanual evaluation following unimanual training. There was no difference in performance following symmetric or asymmetric training. Changing the arm force symmetry during bimanual movements from asymmetric to symmetric had little influence on performance., Conclusions: Subjects could adapt to an unknown disturbance torque that was changing the dynamics of the movements. The learning effect was present during both unimanual and bimanual training. Transfer of learned skills from bimanual training to unimanual movements was also observed, as bimanual training also improved single limb performance with the dominant arm. Changes of force symmetry did not have an effect on motor learning. As motor learning is believed to be an important mechanism of rehabilitation, our findings could be tested for future post-stroke rehabilitation systems.

This paper examines the usefulness of psychophysiological measurements in a biocooperative feedback loop that adjusts the difficulty of an upper extremity rehabilitation task. Psychophysiological measurements (heart rate, skin conductance, respiration, and skin temperature) were used both by themselves and in combination with task performance and biomechanics. Data fusion was performed with discriminant analysis, and a special adaptive version was implemented that can gradually adapt to a subject. Both healthy subjects and hemiparetic patients participated in the study. The accuracy of the biocooperative controller was defined as the percentage of times it matched the subjects' preferences. The highest accuracy rate was obtained for task performance (approximately 82% for both healthy subjects and patients), with psychophysiological measurements yielding relatively low accuracy (approximately 60%). The adaptive approach increased accuracy of psychophysiological measurements to 76.4% for healthy subjects and 68.8% for patients. Combining psychophysiology with task performance yielded an accuracy rate of 84.7% for healthy subjects and 89.4% for patients. Results suggest that psychophysiological measurements are not reliable as a primary data source in motor rehabilitation, but can provide supplementary information. However, it is questionable whether the amount of additional information justifies the increased complexity of the system., (© 2011 IEEE)

Psychological states such as mood, motivation and engagement are known to be critical for the success of rehabilitation, and encouraging unmotivated stroke patients improves the likelihood of their eventual recovery. Psychological factors can be incorporated into the closed-loop control of biocooperative rehabilitation systems, augmenting the device with critical information about the patient state. However, in rehabilitation robotics, interpretation of psychophysiological measurements is made complex by the multi-task environment, the presence of strenuous physical activity and patient's damage to the central and autonomic nervous systems. The study examines these challenges and proposes possible solutions for implementation in biocooperative control of rehabilitation robots., (© 2011 IEEE)

This paper presents the novel "River" multimodal rehabilitation robotics scenario that includes video, audio and haptic modalities. Elements contributing to intrinsic motivation are carefully joined in the three modalities to increase motivation of the user. The user first needs to perform a motor action, then receives a cognitive challenge that is solved with adequate motor activity. Audio includes environmental sounds, music and spoken instructions or encouraging statements. Sounds and music were classified according to the arousal-valence space. The haptic modality can provide catching, grasping, tunnel or adaptive assistance, all depending on the user's needs. The scenario was evaluated in 16 stroke users, who responded to it favourably according to the Intrinsic Motivation Inventory questionnaire. Additionally, the river multimodal environment seems to elicit higher motivation than a simpler apple pick-and-place multimodal task., (© 2011 IEEE)

This study presents a biocooperative feedback loop where the difficulty of an upper extremity rehabilitation task is adjusted based on four psychophysiological measurements: heart rate, skin conductance, respiration and skin temperature. They are used both by themselves and in combination with task performance and biomechanics. Different variants of linear discriminant analysis are used for data fusion, including a variant that can adjust the fusion rules online and thus gradually adapt to the subject. Both healthy subjects and hemiparetic patients participated in the study. The accuracy rate of the biocooperative controller was defined as the percentage of times it matched the subjects' preferences. Psychophysiological measurements yielded a relatively low accuracy rate by themselves (76.4% for healthy subjects and 68.2% for patients). Task performance, on the other hand, yielded an accuracy rate of approximately 82%. Combining task performance with psychophysiology increased the accuracy rate to 84.7% for healthy subjects and 89.4% for patients. Psychophysiology can thus provide additional information, but factors such as the increased cost and complexity of the system should also be taken into account., (© 2011 IEEE)

Psychophysiological responses have become a valuable tool in human-robot interaction since they provide an objective estimate of the user's psychological state. Unfortunately, their usefulness in rehabilitation robotics is uncertain since they are influenced by both physical activity and pathological conditions such as stroke. We performed psychophysiological measurements in subacute and chronic stroke patients as well as healthy controls during a reaching and grasping exercise task performed in a multimodal virtual environment. Furthermore, we evaluated the differences in kinematic and static parameters between the three groups of subjects. The results of the observed kinematic and static evaluation parameters showed significant differences when different assistive modes enabled the subject to focus on a particular function of the exercise, like reaching or grasping, or coordinated actions that combine reaching and grasping, reflecting the motor abilities of the individual. The analysis of psychophysiological responses suggests that both chronic and subacute stroke subjects have weaker psychophysiological responses than healthy subjects, though the responses of chronic patients have recovered somewhat. This certainly indicates that further studies are needed before psychophysiological responses can be used in clinical practice., (© 2011 IEEE)

The paper presents the background, main achievements and components of rehabilitation robotics in a simple way, using non-technical terms. The introductory part looks at the development of robotic approaches in the rehabilitation of neurological patients and outlines the principles of robotic device interactions with patients. There follows a section on virtual reality in rehabilitation. Hapticity and interaction between robot and human are presented in order to understand the added value of robotics that cannot be exploited in other devices. The importance of passive exercise and active tasks is then discussed using the results of various clinical trials, followed by the place of upper and lower extremity robotic devices in rehabilitation practice. The closing section refers to the general importance of measurements in this area and stresses quantitative measurements as one of the advantages in using robotic devices.

Background: Robotic systems are becoming increasingly common in upper extremity stroke rehabilitation. Recent studies have already shown that the use of rehabilitation robots can improve recovery. This paper evaluates the effect of different modes of robot-assistances in a complex virtual environment on the subjects' ability to complete the task as well as on various haptic parameters arising from the human-robot interaction., Methods: The MIMICS multimodal system that includes the haptic robot HapticMaster and a dynamic virtual environment is used. The goal of the task is to catch a ball that rolls down a sloped table and place it in a basket above the table. Our study examines the influence of catching assistance, pick-and-place movement assistance and grasping assistance on the catching efficiency, placing efficiency and on movement-dependent parameters: mean reaching forces, deviation error, mechanical work and correlation between the grasping force and the load force., Results: The results with groups of subjects (23 subacute hemiparetic subjects, 10 chronic hemiparetic subjects and 23 control subjects) showed that the assistance raises the catching efficiency and pick-and-place efficiency. The pick-and-place movement assistance greatly limits the movements of the subject and results in decreased work toward the basket. The correlation between the load force and the grasping force exists in a certain phase of the movement. The results also showed that the stroke subjects without assistance and the control subjects performed similarly., Conclusions: The robot-assistances used in the study were found to be a possible way to raise the catching efficiency and efficiency of the pick-and-place movements in subacute and chronic subjects. The observed movement parameters showed that robot-assistances we used for our virtual task should be improved to maximize physical activity.

This paper presents the analysis of four psychophysiological responses in post-stroke upper extremity rehabilitation. The goal was to determine which psychophysiological responses would provide the most reliable information about subjects' psychological states during rehabilitation. Heart rate, skin conductance, respiration, and skin temperature were recorded in a stroke group and a control group during two difficulty levels of a pick-and-place task performed in a virtual environment using a haptic robot and during a cognitive task. Psychophysiological measurements were correlated with results of a self-report questionnaire. All four responses showed significant changes in response to the different tasks. Skin conductance differentiated between the two difficulty levels and was correlated with self-reported arousal in both stroke and control groups. Skin temperature differentiated between the two difficulty levels for the control group, but provided poor results for the stroke group. Heart rate and respiration increased during tasks, but their connection to psychological state was unclear. Results suggest that, of the four measured responses, skin conductance offers the most potential as a psychological state indicator, with other measures providing supplementary information. Psychophysiological measurements could thus be used in closed-loop biocooperative systems that would detect the user's psychological state and change the course of therapy accordingly.

Introduction:   In the present investigation, we applied the whole-hand transcutaneous electrical nerve stimulation (TENS) therapy to two incomplete tetraplegic subjects and assessed their progress with four evaluation methods., Methods:   Two spinal cord injured subjects with spastic upper extremities participated in the study. The TENS therapy was added to their regular treatment. The TENS was delivered to the subject's hands by a conductive glove. The therapy consisted of 20-min sessions each working day during a period of four weeks. The used assessment methods were: maximal force test, force tracking task, Jebsen-Taylor hand function test, and modified Ashworth scale., Results:   The results show increased finger muscle strength, improved motor control and hand function in both patients. The reduction of muscle tone, as assessed by the modified Ashworth scale, was observed in one subject., Discussion:   There was no correlation found between the Jebsen-Taylor test and the maximal force test or force tracking task in this investigation. Assessment methods are complementary to each other as each one adds new or more detailed information about level of impairment., Conclusion:   From the comparison of four evaluation methods, it is evident that different assessments and measurements should be used in order to get better picture of patient's upper extremity impairment., (© 2010 International Neuromodulation Society.)

An objective test for evaluating functional status of the upper limbs (ULs) in patients with muscular distrophy (MD) is presented. The method allows for quantitative assessment of the UL functional state with an emphasis on force exertion capacity. The experimental measurement setup and the methodology for the assessment of maximal exertable force utilizing the Phantom 1.5 haptic interface has been developed. The measurement setup consists of a powerful virtual reality simulator, capable of providing haptic, visual and audio feedback. The patient's task in the virtual environment is goal oriented and includes stretching a virtual spring in six different directions. The Phantom 1.5 haptic interface serves as a kinematic measuring device and as a force feedback generator. By moving the haptic interface control stick the patient exerts the force in six radial directions to the best of his or her abilities. The new test offers numerical as well as graphic results. The method has been applied to 32 MD patients. Several typical force exertion capacity characteristics, affected by neuro-muscular disorders are shown in a quantitative manner. Data mining was used to demonstrate good content validity of the proposed test. The method allows for a quick, accurate, repeatable and objective measurements of the UL force exertion capability.

The historical development of electrical stimulators producing contraction of paralyzed muscles is briefly presented. The influence of electrical stimulation parameters (amplitude of pulses, frequency, pulse duration, and duration of a pulse train) is explained. Special attention is paid to the description of the muscle recruitment curve. The phenomenon of reversed recruitment order, resulting in fatiguing of electrically stimulated muscle, is presented. The properties of surface electrodes (electrode size, polarity, resistance, and distance between electrodes) are examined. The use of surface electrodes made of metal plate or wire mesh, silicone impregnated with rubber, and conductive adhesive gel are discussed. The design of electrical stimulator circuits is also presented.

The paper presents the background, main achievements and components of rehabilitation robotics in a simple way, using non-technical terms. The introductory part looks at the development of robotic approaches in the rehabilitation of neurological patients and outlines the principles of robotic device interactions with patients. There follows a section on virtual reality in rehabilitation. Hapticity and interaction between robot and human are presented in order to understand the added value of robotics that cannot be exploited in other devices. The importance of passive exercise and active tasks is then discussed using the results of various clinical trials, followed by the place of upper and lower extremity robotic devices in rehabilitation practice. The closing section refers to the general importance of measurements in this area and stresses quantitative measurements as one of the advantages in using robotic devices.

The historical development of electrical stimulators producing contraction of paralyzed muscles is briefly presented. The influence of electrical stimulation parameters (amplitude of pulses, frequency, pulse duration, and duration of a pulse train) is explained. Special attention is paid to the description of the muscle recruitment curve. The phenomenon of reversed recruitment order, resulting in fatiguing of electrically stimulated muscle, is presented. The properties of surface electrodes (electrode size, polarity, resistance, and distance between electrodes) are examined. The use of surface electrodes made of metal plate or wire mesh, silicone impregnated with rubber, and conductive adhesive gel are discussed. The design of electrical stimulator circuits is also presented.

Background: One of the main scientific and technological challenges of rehabilitation bioengineering is the development of innovative methodologies, based on the use of appropriate technological devices, for an objective assessment of patients undergoing a rehabilitation treatment. Such tools should be as fast and cheap to use as clinical scales, which are currently the daily instruments most widely used in the routine clinical practice., Methods: A human-centered approach was used in the design and development of a mechanical structure equipped with eight force/torque sensors that record quantitative data during the initiation of a predefined set of Activities of Daily Living (ADL) tasks, in isometric conditions., Results: Preliminary results validated the appropriateness, acceptability and functionality of the proposed platform, that has become now a tool used for clinical research in three clinical centres., Conclusion: This paper presented the design and development of an innovative platform for whole-body force and torque measurements on human subjects. The platform has been designed to perform accurate quantitative measurements in isometric conditions with the specific aim to address the needs for functional assessment tests of patients undergoing a rehabilitation treatment as a consequence of a stroke.The versatility of the system also enlightens several other interesting possible areas of application for therapy in neurorehabilitation, for research in basic neuroscience, and more.

This paper presents an upgrade of a Phantom Premium 1.5 haptic device for use within a functional magnetic resonance imaging (fMRI) environment. A special mechanical extension that allows the haptic device to operate at a safe distance from the high-density magnetic field of an fMRI scanner has been developed. Extended haptic system was subjected to a series of tests to confirm electromagnetic compatibility with the fMRI scanner, for which key results are presented. With this fMRI compatible haptic platform a human brain activation during controlled upper limb movements can be studied. A simple virtual environment reaching task was programmed to study brain motor control functions. At the end preliminary results of an ongoing neurophysiological study are presented.

This paper presents a new method of trajectory planning in rehabilitation robotics. First were measured in healthy subject the pick to place trajectories while haptic robot is in zero impedance space. B-spline approximation is used to mathematically define the measured paths. This trajectory path serves as a central line for the rounding haptic tunnel. In addition to radial elastic and damping force an optional guidance force can be applied along the tunnel to reach the place point. The B-spline control points were observed around the robot and arm workspace. The trajectory path defined with B-splines is compared with minimum jerk and minimum torque defined trajectories. Finally are compared the pick to place movements with and without tunnel use in healthy subject and in stroke hemiplegic patient.

The aim of this study was to perform a preliminary evaluation of a new method for therapeutic exercise of grasping in patients with upper limb disability. The new method combines active voluntary exercise augmented with electrical stimulation and controlled by using force feedback. The feedback has two functions: automatic control of the intensity of electrical stimulation by minimizing the tracking error, and biofeedback to the patient on the computer screen. The force feedback is realized by the use of a newly designed adjustable hand force measuring device, which comprises two force sensors. The therapy requires from patients to volitionally try to open and close the hand while tracking the target on the screen. The system was evaluated in a pilot study in five healthy and two chronic incomplete tetraplegic subjects. Results in healthy subjects were used for reference and for stimulation controller evaluation. The therapy in incomplete tetraplegic subjects of 45-min daily session delivered during four weeks. The results of pilot study show that augmentation of voluntary grip force control with presented system is possible., (© 2008 International Neuromodulation Society.)

This study proposed virtual reality (VR) as a modality of lower-extremities training. A kinematic model of a human body and a corresponding virtual figure were developed, in order to visualize the movements of the subject in a real-time virtual environment on a large display, which represented a virtual mirror. An optical system with active markers was used to assess the movements of a training subject. A preliminary investigation was conducted with a group of healthy male subjects, who performed the stepping-in-place test by tracking the movements of the reference virtual figure, which represented a virtual instructor. Both figures were shown in the virtual mirror at the same time from the desired angle of view. Four stepping tasks featuring different cadences and hip angles were performed, with difficulty levels ranging from easy to demanding. The results obtained included basic kinematic and temporal parameters, which provided quantitative measures of a subject's adaptation to the virtual training environment, and thereby justifying the feasibility of the virtual mirror as a useful system in lower-extremities training applications.

A haptic device with two active degrees-of-freedom and a tendon-driven transmission system was designed, later on constructed, and submitted to testing. It was embodied as a lightweight mechanism with a small workspace that wraps the finger workspace and can generate forces up to 10 N suitable for finger exercise. The control loop and the user application were implemented on a personal computer in the Microsoft Windows environment. Along with the device, application covering several different experiment types was developed. The system was evaluated in a group of stroke patients during a one-month period of therapy. Results for two types of experiments are presented. The progress of the patient affected hand side was found to be greater than for the one nonaffected, however, the mean values of the relevant parameters on the nonaffected side of patients are higher than those for the affected side. Results were compared to the motor component of functional independence measure (M-FIM) measured clinical scale.

Objective: To show that it is possible to determine segment masses and segment centers of mass by measuring manipulator-hand contact forces and joint angles during upper extremity movement., Background: The method serves as a quick subject specific body segment parameter evaluation technique. Clinically we see this method as an alternative upper extremity body segment parameter evaluation study especially useful in rehabilitation treatment activities., Methods: The experiment is based on coupling the human arm with a robotic manipulator which is then used for imposing a specified sagittal plane trajectory. Joint angles and forces in the contact point serve as input to the identification procedure. For verification purposes the proposed identification procedure was first performed on a mechanical arm. Afterwards a low velocity trajectory was imposed into all joints of the human upper extremity, with very small angular deviations. Within this small angular region the arm was assumed to be represented as a linear system., Findings: The outcome of the identification procedure is an estimate of masses and center of mass coordinates for the lower arm and palm segments, their products for the upper arm and the passive moments around the measured angle of all joints in the sagittal plane. The results obtained for three particular human arms are eventually compared to the average population based literature., Conclusion: From the clinical point of view the study can become useful for biomechanical evaluation and for evaluating biomechanical properties of lower extremities or other body segments. This method may also provide a foundation to measuring body segment moments of inertia and joint viscoelastic parameters.

In the past, limited unsupported standing has been restored in patients with thoracic spinal cord injury through open-loop functional electrical stimulation of paralyzed knee extensor muscles and the support of intact arm musculature. Here an optimal control system for paralyzed ankle muscles was designed that enables the subject to stand without hand support in a sagittal plane. The paraplegic subject was conceptualized as an underactuated double inverted pendulum structure with an active degree of freedom in the upper trunk and a passive degree of freedom in the paralyzed ankle joints. Control system design is based on the minimization of a cost function that estimates the effort of ankle joint muscles via observation of the ground reaction force position, relative to ankle joint axis. Furthermore, such a control system integrates voluntary upper trunk activity and artificial control of ankle joint muscles, resulting in a robust standing posture. Figures are shown for the initial simulation study, followed by disturbance tests on an intact volunteer and several laboratory trials with a paraplegic person. Benefits of the presented methodology are prolonged standing sessions and in the fact that the subject is able to maintain voluntary control over upper body orientation in space, enabling simple functional standing.