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The relationship between motor cortex (M1) and upper limb movements has been investigated extensively using functional MRI (fMRI). While most research has focused on applications, very few studies have focused on practical aspects related to developing the fMRI protocol. Thus, the effect of scan length on M1 activations during various upper limb movements remains unclear. Scan length constraints are important for conducting motor experiments within a 60- or 90-min scan session. We targeted this gap by studying 7T fMRI activations in a male participant while performing eight different upper limb movements (of the fingers, wrist, and elbow) across 16 task runs (8 with the left arm, 8 with the right arm, 88 mins total fMRI duration). Standard activation analyses were performed (Z>3.1, pone size does not fit all’ practical protocol within a 60-, 75-, or 90-min scan session, wherein different number of runs are assigned for different movements. Our study could benefit researchers who are designing upper limb fMRI experiments.

For persons with lower extremity (LE) amputation, acquisition of surface electromyography (sEMG) from within the prosthetic socket remains a significant challenge due to the dynamic loads experienced during the gait cycle. However, these signals are critical for both understanding the clinical effects of LE amputation and determining the desired control trajectories of active LE prostheses. Current solutions for collecting within-socket sEMG are generally (i) incompatible with a subject's prescribed prosthetic socket and liners, (ii) uncomfortable, and (iii) expensive. This study presents an alternative within-socket sEMG acquisition paradigm using a novel flexible and low-profile electrode. First, the practical performance of this Sub-Liner Interface for Prosthetics (SLIP) electrode is compared to that of commercial Ag/AgCl electrodes within a cohort of subjects without amputation. Then, the corresponding SLIP electrode sEMG acquisition paradigm is implemented in a single subject with unilateral transtibial amputation performing unconstrained movements and walking on level ground. Finally, a quantitative questionnaire characterizes subjective comfort for SLIP electrode and commercial Ag/AgCl electrode instrumentation setups. Quantitative analyses suggest comparable signal qualities between SLIP and Ag/AgCl electrodes while qualitative analyses suggest the feasibility of using the SLIP electrode for real-time sEMG data collection from load-bearing, ambulatory subjects with LE amputation.

Objective: This study describes the development and offline validation of a heuristic algorithm for accurate prediction of ground terrain in a lower limb prosthesis. This method is based on inference of the ground terrain geometry using estimation of prosthetic limb kinematics during gait with a single integrated inertial measurement unit. Methods: We asked five subjects with below-knee amputations to traverse level ground, stairs, and ramps using a high-range-of-motion powered prosthesis while internal sensor data were remotely logged. We used these data to develop three terrain prediction algorithms. The first two employed state-of-the-art machine learning approaches, while the third was a directly tuned heuristic using thresholds on estimated prosthetic ankle joint translations and ground slope. We compared the performance of these algorithms using resubstitution error for the machine learning algorithms and overall error for the heuristic algorithm. Results: Our optimal machine learning algorithm attained a resubstitution error of $3.4\%$ using 45 features, while our heuristic method attained an overall prediction error of $2.8\%$ using only 5 features derived from estimation of ground slope and horizontal and vertical ankle joint displacement. Compared with pattern recognition, the heuristic performed better on each individual subject, and across both level and non-level strides. Conclusion and significance: These results demonstrate a method for heuristic prediction of ground terrain in a powered prosthesis. The method is more accurate, more interpretable, and less computationally expensive than machine learning methods considered state-of-the-art for intent recognition, and relies only on integrated prosthesis sensors. Finally, the method provides intuitively tunable thresholds to improve performance for specific walking conditions.

Amputation destroys sensory end organs and does not provide an anatomical interface for cutaneous neuroprosthetic feedback. Here, we report the design and a biomechanical and electrophysiological evaluation of the cutaneous mechanoneural interface consisting of an afferent neural system that comprises a muscle actuator coupled to a natively pedicled skin flap in a cuff-like architecture. Muscle is actuated through electrical stimulation to induce strains or oscillatory vibrations on the skin flap that are proportional to a desired contact duration or contact pressure. In rat hindlimbs, the mechanoneural interface elicited native dermal mechanotransducers to generate at least four levels of graded contact and eight distinct vibratory afferents that were not significantly different from analogous mechanical stimulation of intact skin. The application of different patterns of electrical stimulation independently engaged slowly adapting and rapidly adapting mechanotransducers, and recreated an array of cutaneous sensations. The cutaneous mechanoneural interface can be integrated with current prosthetic technologies for tactile feedback. A neuroprosthetic interface comprising a muscle actuator coupled to a natively pedicled skin flap in a cuff-like architecture elicits graded contact and vibratory afferent signals analogous to those elicited by mechanical stimulation of intact skin.

BackgroundFunctional magnetic resonance imaging (fMRI) provides critical information about the neurophysiology of the central nervous systems (CNS), posing clinical significance for the understanding of neuropathologies and advancement of rehabilitation. Typical fMRI study designs include subjects performing designed motor tasks within specific time frames, in which fMRI data are then analyzed by assuming that observed functional brain activations correspond to the designed tasks. Therefore, developing MRI-compatible sensors that enable real-time monitoring of subjects’ task performances would allow for highly accurate fMRI studies. While several MRI-compatible sensors have been developed, none have demonstrated the ability to measure individual muscle fascicle length during fMRI, which could help uncover the complexities of the peripheral and central nervous systems. Furthermore, previous MRI-compatible sensors have been focused on biologically intact populations, limiting accessibility to populations such as those who have undergone amputation.MethodsWe propose a lightweight, low-cost, skin impedance-insensitive pressure-based muscular motion sensor (pMMS) that provides reliable estimates of muscle fascicle length and joint angle. The muscular motions are captured through measured pressure changes in an air pocket wrapped around the muscle of interest, corresponding to its muscular motion. The muscle fascicle length and joint angle are then estimated from the measured pressure changes based on the proposed muscle-skin-sensor interaction dynamics. Furthermore, we explore an integration method of multiple pMMS systems to expand the sensor capacity of estimating muscle fascicle length and joint angle. Ultrasound imaging paired with joint encoder measurements are utilized to assess pMMS estimation accuracy of muscle fascicle length in the tibialis anterior (TA) and ankle joint angle, respectively, of five biologically intact subjects.ResultsWe found that a single pMMS sufficiently provides robust and accurate estimations of TA muscle fascicle length and ankle joint angle during dorsiflexion at various speeds and amplitudes. Further, differential pressure readings from two pMMSs, in which each pMMS were proximally and distally placed, were able to mitigate errors due to perturbations, expanding pMMS capacity for muscle fascicle length and ankle joint angle estimation during the full range of plantar flexion and dorsiflexion.ConclusionsOur results from this study demonstrate the feasibility of the pMMS system to further be incorporated in fMRI settings for real-time monitoring of subjects’ task performances, allowing sophisticated fMRI study designs.

Lower-limb assisted exoskeletons are widely researched for movement assistance or rehabilitation training. Due to advantages of compliance with human body and lightweight, some cable-driven prototypes have been developed, but most of these can assist only unidirectional movement. In this paper we present an untethered cable-driven ankle exoskeleton that can achieve plantarflexion-dorsiflexion bidirectional motion bilaterally using a pair of single motors. The main weights of the exoskeleton, i.e., the motors, power supplement units, and control units, were placed close to the proximity of the human body, i.e., the waist, to reduce the redundant rotation inertia which would apply on the wearer’s leg. A cable force transmission system based on gear-pulley assemblies was designed to transfer the power from the motor to the end-effector effectively. A cable self-tension device on the power output unit was designed to tension the cable during walking. The gait detection system based on a foot pressure sensor and an inertial measurement unit (IMU) could identify the gait cycle and gait states efficiently. To validate the power output performance of the exoskeleton, a torque tracking experiment was conducted. When the subject was wearing the exoskeleton with power on, the muscle activity of the soleus was reduced by 5.2% compared to the state without wearing the exoskeleton. This preliminarily verifies the positive assistance effect of our exoskeleton. The study in this paper demonstrates the promising application of a lightweight cable-driven exoskeleton on human motion augmentation or rehabilitation.

Finite element analysis (FEA) can be used to evaluate applied interface pressures and internal tissue strains for computational prosthetic socket design. This type of framework requires realistic patient-specific limb geometry and constitutive properties. In recent studies, indentations and inverse FEA with MRI-derived 3D patient geometries were used for constitutive parameter identification. However, long computational times and use of specialized equipment presents challenges for clinical, deployment. In this study, we present a novel approach for constitutive parameter identification using a combination of FEA, ultrasound indentation, and shear wave elastography. Local shear modulus measurement using elastography during an ultrasound indentation experiment has particular significance for biomechanical modeling of the residual limb since there are known regional dependencies of soft tissue properties such as varying levels of scarring and atrophy. Beyond prosthesis design, this work has broader implications to the fields of muscle health and monitoring of disease progression.

© 2001-2012 IEEE. Magnetic target tracking is a low-cost, portable, and passive method for tracking materials wherein magnets are physically attached or embedded without the need for line of sight. Traditional magnet tracking techniques use optimization algorithms to determine the positions and orientations of permanent magnets from magnetic field measurements. However, such techniques are constrained by high latencies, primarily due to the numerical calculation of the gradient. In this study, we derive the analytic gradient for multiple-magnet tracking and show a dramatic reduction in tracking latency. We design a physical system comprising an array of magnetometers and one or more spherical magnets. To validate the performance of our tracking algorithm, we compare the magnet tracking estimates with state-of-the-art motion capture measurements for each of four distinct magnet sizes. We find comparable position and orientation errors to state-of-the-art magnet tracking, but demonstrate increased maximum bandwidths of 336%, 525%, 635%, and 773% for the simultaneous tracking of 1, 2, 3, and 4 magnets, respectively. We further show that it is possible to extend the analytic gradient to account for disturbance fields, and we demonstrate the simultaneous tracking of 1 to 4 magnets with disturbance compensation. These findings extend the use of magnetic target tracking to high-speed, real-time applications requiring the tracking of one or more targets without the constraint of a fixed magnetometer array. This advancement enables applications such as low-latency augmented and virtual reality interaction, volitional or reflexive control of prostheses and exoskeletons, and simplified multi-degree-of-freedom magnetic levitation.

Scientist and technologist have long sought to advance limb prostheses that connect directly to the peripheral nervous system, enabling a person with amputation to volitionally control synthetic actuators that move, stiffen and power the prosthesis, as well as to experience natural afferent sensations from the prosthesis. Recently, the agonist-antagonist myoneural interface (AMI) was developed, a mechanoneural transduction architecture and neural interface system designed to provide persons with amputation improved muscle-tendon proprioception and neuroprosthetic control. In this paper, we provide an overview of the AMI, including its conceptual framing and pre-clinical science, surgical techniques for its construction, and clinical efficacy related to pain mitigation, phantom limb range of motion, fascicle dynamics, central brain proprioceptive sensorimotor preservation, and prosthetic controllability. Following this broad overview, we end with a discussion of current limitations of the AMI and potential resolutions to such challenges.

Neuroprosthetic devices controlled by persons with standard limb amputation often lack the dexterity of the physiological limb due to limitations of both the user's ability to output accurate control signals and the control system's ability to formulate dynamic trajectories from those signals. To restore full limb functionality to persons with amputation, it is necessary to first deduce and quantify the motor performance of the missing limbs, then meet these performance requirements through direct, volitional control of neuroprosthetic devices.We develop a neuromuscular modeling and optimization paradigm for the agonist-antagonist myoneural interface, a novel tissue architecture and neural interface for the control of myoelectric prostheses, that enables it to generate virtual joint trajectories coordinated with an intact biological joint at full physiologically-relevant movement bandwidth. In this investigation, a baseline of performance is first established in a population of non-amputee control subjects ([Formula: see text]). Then, a neuromuscular modeling and optimization technique is advanced that allows unilateral AMI amputation subjects ([Formula: see text]) and standard amputation subjects ([Formula: see text]) to generate virtual subtalar prosthetic joint kinematics using measured surface electromyography (sEMG) signals generated by musculature within the affected leg residuum.Using their optimized neuromuscular subtalar models under blindfolded conditions with only proprioceptive feedback, AMI amputation subjects demonstrate bilateral subtalar coordination accuracy not significantly different from that of the non-amputee control group (Kolmogorov-Smirnov test, [Formula: see text]) while standard amputation subjects demonstrate significantly poorer performance (Kolmogorov-Smirnov test, [Formula: see text]).These results suggest that the absence of an intact biological joint does not necessarily remove the ability to produce neurophysical signals with sufficient information to reconstruct physiological movements. Further, the seamless manner in which virtual and intact biological joints are shown to coordinate reinforces the theory that desired movement trajectories are mentally formulated in an abstract task space which does not depend on physical limb configurations.

Significance Despite advancements in prosthetic technologies, persons with amputation today suffer great diminution in mobility and quality of life. This is largely due to an outdated amputation paradigm that precludes efficacious communication between the residual limb and prosthesis. An amputation method utilizing agonist–antagonist myoneural interfaces (AMIs) constructs neuromuscular substrates in the residual limb to avail enhanced sensorimotor signaling. In our study, subjects with AMI amputation demonstrate improved motor control, phantom sensations, range of motion, and decreased pain when compared to patients with traditional amputation. With the demonstrated increases in motor coordination and position differentiation, our results suggest that patients with AMI amputation will be able to more efficaciously control bionic prostheses., Despite advancements in prosthetic technologies, patients with amputation today suffer great diminution in mobility and quality of life. We have developed a modified below-knee amputation (BKA) procedure that incorporates agonist–antagonist myoneural interfaces (AMIs), which surgically preserve and couple agonist–antagonist muscle pairs for the subtalar and ankle joints. AMIs are designed to restore physiological neuromuscular dynamics, enable bidirectional neural signaling, and offer greater neuroprosthetic controllability compared to traditional amputation techniques. In this prospective, nonrandomized, unmasked study design, 15 subjects with AMI below-knee amputation (AB) were matched with 7 subjects who underwent a traditional below-knee amputation (TB). AB subjects demonstrated significantly greater control of their residual limb musculature, production of more differentiable efferent control signals, and greater precision of movement compared to TB subjects (P < 0.008). This may be due to the presence of greater proprioceptive inputs facilitated by the significantly higher fascicle strains resulting from coordinated muscle excursion in AB subjects (P < 0.05). AB subjects reported significantly greater phantom range of motion postamputation (AB: 12.47 ± 2.41, TB: 10.14 ± 1.45 degrees) when compared to TB subjects (P < 0.05). Furthermore, AB subjects also reported less pain (12.25 ± 5.37) than TB subjects (17.29 ± 10.22) and a significant reduction when compared to their preoperative baseline (P < 0.05). Compared with traditional amputation, the construction of AMIs during amputation confers the benefits of enhanced physiological neuromuscular dynamics, proprioception, and phantom limb perception. Subjects’ activation of the AMIs produces more differentiable electromyography (EMG) for myoelectric prosthesis control and demonstrates more positive clinical outcomes.