Estimates of persistent inward current in human motor neurons during postural sway

Persistent inward current (PIC) is a membrane property critical for increasing gain of motor neuron output. In humans, most estimates of PIC are made from plantarflexor or dorsiflexor motor units with the participant in a seated position with the knee flexed. This seated and static posture neglects the task-dependent nature of the monoaminergic drive that modulates PIC activation. Seated estimates may drastically underestimate the amount of PIC that occurs in human motor neurons during functional movement. The current study estimated PIC using the conventional paired motor unit technique which uses the difference between reference unit firing frequency at test unit recruitment and reference unit firing frequency at test unit de-recruitment (∆F) during triangular-shaped, isometric ramps in plantarflexion force as an estimate of PIC. Estimates of PIC were also made during standing anterior postural sway, a postural task that elicits a ramped increase and decrease in soleus motor unit activation similar to the conventional seated ramp contractions. For each motor unit pair, ∆F estimates of PIC made during conventional isometric ramps in the seated posture were compared to those made during standing postural sway. Baseline reciprocal inhibition (RI) was also measured in each posture using the post-stimulus time histogram (PSTH) technique. Hyperpolarizing input has been shown to have a reciprocal relationship with PIC in seated posture and RI was measured to examine if the same reciprocal relationship holds true during functional PIC estimation. It was hypothesized that an increase in ∆F would be seen during standing compared to sitting due to greater neuromodulatory input. We found that ∆F estimates during standing postural sway were equal (2.44 ± 1.17, p=0.44) to those in seated PIC estimates (2.73± 1.20) using the same motor unit pair. Reciprocal inhibition was significantly lower when measured in a standing posture (0.0031 ± 0.0251,

Time course of functional recovery during the first 3 mo after surgical transection and repair of nerves to the feline soleus and lateral gastrocnemius muscles

Locomotion outcomes after peripheral nerve injury and repair in cats have been described in the literature for the period immediately following the injury (muscle denervation period) and then again for an ensuing period of long-term recovery (at 3 mo and longer) resulting in muscle self-reinnervation. Little is known about the changes in muscle activity and walking mechanics during midrecovery, i.e., the early reinnervation period that takes place between 5 and 10 wk of recovery. Here, we investigated hindlimb mechanics and electromyogram (EMG) activity of ankle extensors in six cats during level and slope walking before and every 2 wk thereafter in a 14-wk period of recovery after the soleus (SO) and lateral gastrocnemius (LG) muscle nerves in one hindlimb were surgically transected and repaired. We found that the continued increase in SO and LG EMG magnitudes and corresponding changes in hindlimb mechanics coincided with the formation of neuromuscular synapses revealed in muscle biopsies. Throughout the recovery period, EMG magnitude of SO and LG during the stance phase and the duration of the stance-related activity were load dependent, similar to those in the intact synergistic medial gastrocnemius and plantaris. These results and the fact that EMG activity of ankle extensors and locomotor mechanics during level and upslope walking recovered 14 wk after nerve transection and repair suggest that loss of the stretch reflex in self-reinnervated muscles may be compensated by the recovered force-dependent feedback in self-reinnervated muscles, by increased central drive, and by increased gain in intermuscular motion-dependent pathways from intact ankle extensors. NEW & NOTEWORTHY This study provides new evidence that the timeline for functional recovery of gait after peripheral nerve injury and repair is consistent with the time required for neuromuscular junctions to form and muscles to reach preoperative tensions. Our findings suggest that a permanent loss of autogenic stretch reflex in self-reinnervated muscles may be compensated by recovered intermuscular force-dependent and oligosynaptic length-dependent feed-back and central drive to regain adequate locomotor output capabilities during level and upslope walking

Nineteenth Annual Conference on Manual Control

No abstract availabl

Functional organization of cutaneous reflex pathways during locomotion and reorganization following peripheral nerve and/or spinal cord lesions

Thèse numérisée par la Division de la gestion de documents et des archives de l'Université de Montréal

Advancing Medical Technology for Motor Impairment Rehabilitation: Tools, Protocols, and Devices

Excellent motor control skills are necessary to live a high-quality life. Activities such as walking, getting dressed, and feeding yourself may seem mundane, but injuries to the neuromuscular system can render these tasks difficult or even impossible to accomplish without assistance. Statistics indicate that well over 100 million people are affected by diseases or injuries, such as stroke, Parkinson’s Disease, Multiple Sclerosis, Cerebral Palsy, peripheral nerve injury, spinal cord injury, and amputation, that negatively impact their motor abilities. This wide array of injuries presents a challenge to the medical field as optimal treatment paradigms are often difficult to implement due to a lack of availability of appropriate assessment tools, the inability for people to access the appropriate medical centers for treatment, or altogether gaps in technology for treating the underlying impairments causing the disability. Addressing each of these challenges will improve the treatment of movement impairments, provide more customized and continuous treatment to a larger number of patients, and advance rehabilitative and assistive device technology. In my research, the key approach was to develop tools to assess and treat upper extremity movement impairment. In Chapter 2.1, I challenged a common biomechanical[GV1] modeling technique of the forearm. Comparing joint torque values through inverse dynamics simulation between two modeling platforms, I discovered that representing the forearm as a single cylindrical body was unable to capture the inertial parameters of a physiological forearm which is made up of two segments, the radius and ulna. I split the forearm segment into a proximal and distal segment, with the rationale being that the inertial parameters of the proximal segment could be tuned to those of the ulna and the inertial parameters of the distal segment could be tuned to those of the radius. Results showed a marked increase in joint torque calculation accuracy for those degrees of freedom that are affected by the inertial parameters of the radius and ulna. In Chapter 2.2, an inverse kinematic upper extremity model was developed for joint angle calculations from experimental motion capture data, with the rationale being that this would create an easy-to-use tool for clinicians and researchers to process their data. The results show accurate angle calculations when compared to algebraic solutions. Together, these chapters provide easy-to-use models and tools for processing movement assessment data. In Chapter 3.1, I developed a protocol to collect high-quality movement data in a virtual reality task that is used to assess hand function as part of a Box and Block Test. The goal of this chapter is to suggest a method to not only collect quality data in a research setting but can also be adapted for telehealth and at home movement assessment and rehabilitation. Results indicate that the data collected in this protocol are good and the virtual nature of this approach can make it a useful tool for continuous, data driven care in clinic or at home. In Chapter 3.2 I developed a high-density electromyography device for collecting motor unit action potentials of the arm. Traditional surface electromyography is limited by its ability to obtain signals from deep muscles and can also be time consuming to selectively place over appropriate muscles. With this high-density approach, muscle coverage is increased, placement time is decreased, and deep muscle activity can potentially be collected due to the high-density nature of the device[GV2] . Furthermore, the high-density electromyography device is built as a precursor to a high-density electromyography-electrical stimulation device for functional electrical stimulation. The customizable nature of the prototype in Chapter 3.2 allows for the implementation both recording and stimulating electrodes. Furthermore, signal results show that the electromyography data obtained from the device are of high quality and are correlated with gold standard surface electromyography sensors. One key factor in a device that can record and then stimulate based on the information from the recorded signals is an accurate movement intent decoder. High-quality movement decoders have been designed by closed-loop device controllers in the past, but they still struggle when the user interacts with objects of varying weight due to underlying alterations in muscle signals. In Chapter 4, I investigate this phenomenon by administering an experiment where participants perform a Box and Block Task with objects of 3 different weights, 0 kg, 0.02 kg, and 0.1 kg. Electromyography signals of the participants right arm were collected and co-contraction levels between antagonistic muscles were analyzed to uncover alterations in muscle forces and joint dynamics. Results indicated contraction differences between the conditions and also between movement stages (contraction levels before grabbing the block vs after touching the block) for each condition. This work builds a foundation for incorporating object weight estimates into closed-loop electromyography device movement decoders. Overall, we believe the chapters in this thesis provide a basis for increasing availability to movement assessment tools, increasing access to effective movement assessment and rehabilitation, and advance the medical device and technology field

Doctor of Philosophy

dissertationMedical intervention to restore motor function lost due to injury, stroke, or disease is increasingly common. Recent research in this field, known as functional electrical stimulation (FES), has produced a new generation of electrode devices that greatly enhance selectivity of access to neural populations, enabling-for the first time-restoration of motor function approaching what healthy humans enjoy. Research with these devices, however, has been severely hampered by the lack of a stimulation platform and control algorithms capable of exploring their full potential. The following dissertation presents the results of research aimed at addressing this problem. A major theme of this work is the use of software algorithms and analysis principles to facilitate both investigation and control of the motor system. Though many of the algorithms are well known in computer science, their application to the field of motor restoration is novel. Associated with use of these algorithms are important methodological considerations such as speed of execution, convergence, and optimality. The first phase of the research involved development of a hardware and software platform designed to support a wide range of closed-loop response mapping and control routines. Software routines to automate three time-consuming tasks-mapping stimulus thresholds, mapping stimulus-response recruitment curves, and mapping electrode pair excitation overlap- were implemented and validated in a cat model. Computer control, combined with the use of an efficient binary search algorithm, reduced the time need to complete required implant mapping tasks by a factor of 4 or more (compared to manual mapping), making feasible-for the first time-acute experiments investigating multi-array, multijoint experimental limb control. The second phase of the research involved investigating the influence of stimulus timing, within multielectrode trains, on the smoothness of evoked muscle responses. A model for predicting responses was developed and used, in conjunction with function optimization techniques, to identify stimulus timings that minimize response variation (ripple). In-vivo validation demonstrated that low-ripple timings can be identified, and that the influence of timing on ripple depends largely on the response kinetics of the motor unit pools recruited by constituent electrodes. The final phase of the research involved using the response prediction model to simulate the behavior of a feedback-based, stimulus-timing adjustment algorithm. Multiple simulations were executed to assess the influence of three algorithm parameters-filter bandwidth, error sampling delay, and timing adjustment gain-on two performance metrics- convergence time and percent reduction in ripple. Results show that all parameters have an influence on algorithm performance. Convergence speed is the metric most a↵ected by parameter adjustment, improving by a factor of more than 3 (13 cycles to approximately 4 cycles). Ripple reduction is also a↵ected-exhibiting a 17% reduction with appropriate selection of error sampling delay. These results demonstrate the value of using this simulation approach for parameter tuning

Feedback control of cycling in spinal cord injury using functional electrical stimulation

This thesis is concerned with the realisation of leg cycling by means of FES in SCI individuals with complete paraplegia. FES lower-limb cycling can be safely performed by paraplegics on static ergometers or recumbent tricycles. In this work, different FES cycling systems were developed for clinical and home use. Two design approaches have been followed. The first is based on the adaptation of commercially available recumbent tricycles. This results in devices which can be used as static trainers or for mobile cycling. The second design approach utilises a commercially available motorised ergometer which can be operated while sitting in a wheelchair. The developed FES cycling systems can be operated in isotonic (constant cycling resistance) or isokinetic mode (constant cadence) when used as static trainers. This represents a novelty compared to existing FES cycling systems. In order to realise isokinetic cycling, an electric motor is needed to assist or resist the cycling movement to maintain a constant cadence. Repetitive control technology is applied to the motor in this context to virtually eliminate disturbance caused by the FES activated musculature which are periodic with respect to the cadence. Furthermore, new methods for feedback control of the patient’s work rate have been introduced. A one year pilot study on FES cycling with paraplegic subjects has been carried out. Effective indoor cycling on a trainer setup could be achieved for long periods up to an hour, and mobile outdoor cycling was performed over useful distances. Power output of FES cycling was in the range of 15 to 20 W for two of the three subjects at the end of the pilot study. A muscle strengthening programme was carried out prior and concurrent to the FES cycling. Feedback control of FES assisted weight lifting exercises by quadriceps stimulation has been studied in this context

Organizing principles underlying the formation of arm trajectories

Thesis (Ph.D.)--Harvard--Massachusetts Institute of Technology Division of Health Sciences and Technology Program in Medical Engineering and Medical Physics, 1983.MICROFICHE COPY AVAILABLE IN ARCHIVES AND SCIENCE.Bibliography: leaves 200-214.by Tamar Yashin-Flash.Ph.D