Predicting muscle forces of individuals with hemiparesis following stroke

Computational Design of FastFES Treatment to Improve Propulsive Force Symmetry During Post-stroke Gait: A Feasibility Study

Stroke is a leading cause of long-term disability worldwide and often impairs walking ability. To improve recovery of walking function post-stroke, researchers have investigated the use of treatments such as fast functional electrical stimulation (FastFES). During FastFES treatments, individuals post-stroke walk on a treadmill at their fastest comfortable speed while electrical stimulation is delivered to two muscles of the paretic ankle, ideally to improve paretic leg propulsion and toe clearance. However, muscle selection and stimulation timing are currently standardized based on clinical intuition and a one-size-fits-all approach, which may explain in part why some patients respond to FastFES training while others do not. This study explores how personalized neuromusculoskeletal models could potentially be used to enable individual-specific selection of target muscles and stimulation timing to address unique functional limitations of individual patients post-stroke. Treadmill gait data, including EMG, surface marker positions, and ground reactions, were collected from an individual post-stroke who was a non-responder to FastFES treatment. The patient's gait data were used to personalize key aspects of a full-body neuromusculoskeletal walking model, including lower-body joint functional axes, lower-body muscle force generating properties, deformable foot-ground contact properties, and paretic and non-paretic leg neural control properties. The personalized model was utilized within a direct collocation optimal control framework to reproduce the patient's unstimulated treadmill gait data (verification problem) and to generate three stimulated walking predictions that sought to minimize inter-limb propulsive force asymmetry (prediction problems). The three predictions used: (1) Standard muscle selection (gastrocnemius and tibialis anterior) with standard stimulation timing, (2) Standard muscle selection with optimized stimulation timing, and (3) Optimized muscle selection (soleus and semimembranosus) with optimized stimulation timing. Relative to unstimulated walking, the optimal control problems predicted a 41% reduction in propulsive force asymmetry for scenario (1), a 45% reduction for scenario (2), and a 64% reduction for scenario (3), suggesting that non-standard muscle selection may be superior for this patient. Despite these predicted improvements, kinematic symmetry was not noticeably improved for any of the walking predictions. These results suggest that personalized neuromusculoskeletal models may be able to predict personalized FastFES training prescriptions that could improve propulsive force symmetry, though inclusion of kinematic requirements would be necessary to improve kinematic symmetry as well.

An approach to a muscle force model with force-pulse amplitude relationship of human quadriceps muscles

BACKGROUND

Recent advanced applications of the functional electrical stimulation (FES) mostly used closed-loop control strategies based on mathematical models to improve the performance of the FES systems. In most of them, the pulse amplitude was used as an input control. However, in controlling the muscle force, the most popular force model developed by Ding et al. does not take into account the pulse amplitude effect. The purpose of this study was to include the pulse amplitude in the existing Ding et al. model based on the recruitment curve function.

METHODS

Quadriceps femoris muscles of eight healthy subjects were tested. Forces responses to stimulation trains with different pulse amplitudes (30-100 mA) and frequencies (20-80 Hz) were recorded and analyzed. Then, specific model parameter values were identified by fitting the measured forces for one train (50 Hz, 100 mA). The obtained model parameters were then used to identify the recruitment curve parameter values by fitting the force responses for different pulse amplitudes at the same frequency train. Finally, the extended model was used to predict force responses for a range of stimulation pulse amplitudes and frequencies.

RESULTS

The experimental results indicated that our adapted model accurately predicts the force-pulse amplitude relationship with an excellent agreement between measured and predicted forces (R²=0.998, RMSE = 6.6 N).

CONCLUSIONS

This model could be used to predict the pulse amplitude effect and to design control strategies for controlling the muscle force in order to obtain precise movements during FES sessions using intensity modulation.

Comparison of functional electrical stimulation associated with kinesiotherapy and kinesiotherapy alone in patients with hemiparesis during the subacute phase of ischemic cerebrovascular accident

OBJECTIVE

To compare the functional electrical stimulation associated with functional kinesiotherapy alone in patients after ischemic cerebrovascular accident.

METHODS

The study included 20 patients who were divided into two groups: Group I (GI): functional electrical stimulation plus functional kinesiotherapy and Group II (GII): functional kinesiotherapy. We evaluated active and passive range of motion, in knee flexion and extension muscle strength, activities of daily living and quality of life. The evaluations were conducted in the pretreatment period, after 10 sessions and after 20 physical therapy sessions.

RESULTS

There was a significant improvement in all variables studied for both groups. However, significant improvements for the sub-items functional capacity and social aspects were seen only in the patients treated with associated functional electrical stimulation and kinesiotherapy.

CONCLUSION

Although both groups of patients improved with the treatment, the association of functional electrical stimulation and kinesiotherapy showed superiority in two quality of life items, in the sub-items functional capacity and social aspects.

Selective activation of the human tibial and common peroneal nerves with a flat interface nerve electrode

OBJECTIVE

Electrical stimulation has been shown effective in restoring basic lower extremity motor function in individuals with paralysis. We tested the hypothesis that a flat interface nerve electrode (FINE) placed around the human tibial or common peroneal nerve above the knee can selectively activate each of the most important muscles these nerves innervate for use in a neuroprosthesis to control ankle motion.

APPROACH

During intraoperative trials involving three subjects, an eight-contact FINE was placed around the tibial and/or common peroneal nerve, proximal to the popliteal fossa. The FINE's ability to selectively recruit muscles innervated by these nerves was assessed. Data were used to estimate the potential to restore active plantarflexion or dorsiflexion while balancing inversion and eversion using a biomechanical simulation.

MAIN RESULTS

With minimal spillover to non-targets, at least three of the four targets in the tibial nerve, including two of the three muscles constituting the triceps surae, were independently and selectively recruited in all subjects. As acceptable levels of spillover increased, recruitment of the target muscles increased. Selective activation of muscles innervated by the peroneal nerve was more challenging.

SIGNIFICANCE

Estimated joint moments suggest that plantarflexion sufficient for propulsion during stance phase of gait and dorsiflexion sufficient to prevent foot drop during swing can be achieved, accompanied by a small but tolerable inversion or eversion moment.

Using submaximal contractions to predict the maximum force-generating ability of muscles

INTRODUCTION

Muscle weakness can be caused by decreases in either the maximum force-generating ability of a muscle (MFGA) or neural drive from the nervous system (e.g., after a stroke). Presently, there is no agreed-upon practical method for calculating the MFGA in individuals with central nervous system pathology. The purpose of this study was to identify the best method for determining MFGA.

METHODS

The predicted and estimated MFGA of the muscles of 23 non-neurologically impaired subjects (13 males, 21.9 ± 1.9 years) were compared using the burst superimposition, twitch interpolation, doublet interpolation, twitch-to-tetanus ratio, and the adjusted burst superimposition methods.

RESULTS

The adjusted burst superimposition test was the most accurate predictor of MFGA.

CONCLUSIONS

Further testing is needed to validate the use of the adjusted burst superimposition test in a neurologically impaired population.

Design of Optimal Treatments for Neuromusculoskeletal Disorders using Patient-Specific Multibody Dynamic Models

Disorders of the human neuromusculoskeletal system such as osteoarthritis, stroke, cerebral palsy, and paraplegia significantly affect mobility and result in a decreased quality of life. Surgical and rehabilitation treatment planning for these disorders is based primarily on static anatomic measurements and dynamic functional measurements filtered through clinical experience. While this subjective treatment planning approach works well in many cases, it does not predict accurate functional outcome in many others. This paper presents a vision for how patient-specific multibody dynamic models can serve as the foundation for an objective treatment planning approach that identifies optimal treatments and treatment parameters on an individual patient basis. First, a computational paradigm is presented for constructing patient-specific multibody dynamic models. This paradigm involves a combination of patient-specific skeletal models, muscle-tendon models, neural control models, and articular contact models, with the complexity of the complete model being dictated by the requirements of the clinical problem being addressed. Next, three clinical applications are presented to illustrate how such models could be used in the treatment design process. One application involves the design of patient-specific gait modification strategies for knee osteoarthritis rehabilitation, a second involves the selection of optimal patient-specific surgical parameters for a particular knee osteoarthritis surgery, and the third involves the design of patient-specific muscle stimulation patterns for stroke rehabilitation. The paper concludes by discussing important challenges that need to be overcome to turn this vision into reality.