Muscle Stimulation Waveform Timing Patterns for Upper and Lower Leg Muscle Groups to Increase Muscular Endurance in Functional Electrical Stimulation Pedaling Using a Forward Dynamic Model

2009 ◽  
Vol 56 (9) ◽  
pp. 2263-2270 ◽  
Author(s):  
Nils A. Hakansson ◽  
M. L. Hull
Keyword(s):  
Electrical Stimulation ◽  
Dynamic Model ◽  
Functional Electrical Stimulation ◽  
Lower Leg ◽  
Muscle Stimulation ◽  
Muscular Endurance ◽  
Leg Muscle ◽  
Muscle Groups

scholarly journals Evaluation of Individualized Functional Electrical Stimulation-Induced Acute Changes during Walking: A Case Series in Children with Cerebral Palsy

Sensors ◽  
2021 ◽  
Vol 21 (13) ◽  
pp. 4452
Author(s):  
Nicole Zahradka ◽  
Ahad Behboodi ◽  
Ashwini Sansare ◽  
Samuel C. K. Lee
Keyword(s):  
Cerebral Palsy ◽  
Electrical Stimulation ◽  
Functional Electrical Stimulation ◽  
Physical Therapists ◽  
Physical Therapist ◽  
Case Series ◽  
Phase Detection ◽  
Lower Extremity Muscle ◽  
Children With Cerebral Palsy ◽  
Muscle Groups

Functional electrical stimulation (FES) walking interventions have demonstrated improvements to gait parameters; however, studies were often confined to stimulation of one or two muscle groups. Increased options such as number of muscle groups targeted, timing of stimulation delivery, and level of stimulation are needed to address subject-specific gait deviations. We aimed to demonstrate the feasibility of using a FES system with increased stimulation options during walking in children with cerebral palsy (CP). Three physical therapists designed individualized stimulation programs for six children with CP to target participant-specific gait deviations. Stimulation settings (pulse duration and current) were tuned to each participant. Participants donned our custom FES system that utilized gait phase detection to control stimulation to lower extremity muscle groups and walked on a treadmill at a self-selected speed. Motion capture data were collected during walking with and without the individualized stimulation program. Eight gait metrics and associated timing were compared between walking conditions. The prescribed participant-specific stimulation programs induced significant change towards typical gait in at least one metric for each participant with one iteration of FES-walking. FES systems with increased stimulation options have the potential to allow the physical therapist to better target the individual’s gait deviations than a one size fits all device.

scholarly journals Probability-Based Prediction of Activity in Multiple Arm Muscles: Implications for Functional Electrical Stimulation

2008 ◽  
Vol 100 (1) ◽  
pp. 482-494 ◽  
Author(s):  
Chad V. Anderson ◽  
Andrew J. Fuglevand
Keyword(s):  
Electrical Stimulation ◽  
Functional Electrical Stimulation ◽  
Muscle Activity ◽  
Probability Distributions ◽  
Probabilistic Methods ◽  
Muscle Stimulation ◽  
Implanted Electrodes ◽  
Motor Behaviors ◽  
Wide Range ◽  
Arm Muscles

Functional electrical stimulation (FES) involves artificial activation of muscles with implanted electrodes to restore motor function in paralyzed individuals. The range of motor behaviors that can be generated by FES, however, is limited to a small set of preprogrammed movements such as hand grasp and release. A broader range of movements has not been implemented because of the substantial difficulty associated with identifying the patterns of muscle stimulation needed to elicit specified movements. To overcome this limitation in controlling FES systems, we used probabilistic methods to estimate the levels of muscle activity in the human arm during a wide range of free movements based on kinematic information of the upper limb. Conditional probability distributions were generated based on hand kinematics and associated surface electromyographic (EMG) signals from 12 arm muscles recorded during a training task involving random movements of the arm in one subject. These distributions were then used to predict in four other subjects the patterns of muscle activity associated with eight different movement tasks. On average, about 40% of the variance in the actual EMG signals could be accounted for in the predicted EMG signals. These results suggest that probabilistic methods ultimately might be used to predict the patterns of muscle stimulation needed to produce a wide array of desired movements in paralyzed individuals with FES.

scholarly journals Periodik Paralisis Hipokalemia pada Anak Usia 15

2020 ◽  
Vol 20 (2) ◽  
Author(s):  
Jufitriani Ismy
Keyword(s):  
Key Words ◽  
Clinical Symptom ◽  
Muscle Weakness ◽  
Lower Leg ◽  
Periodic Paralysis ◽  
Progressive Muscle Weakness ◽  
Leg Muscle ◽  
Acute Attacks ◽  
Muscle Groups

Abstrak. Periodik paralisis hipokalemia menyebabkan kelemahan otot yang progresif terutama pada kelompok otot proksimal tungkai bawah, serangan akut dapat terjadi secara berulang. Serangan pertama biasanya terjadi antara usia 5 tahun dan 35 tahun, tetapi frekuensi serangan paling tinggi antara usia 15 dan 35 tahun.  Ditemukan kasus Periodik paralisis hipokalemia yang berulang pada anak laki laki usia 15 tahun. Semua hasil analisis gejala klinis dan pemeriksaan penunjang sangat mendukung untuk diagnosis periodik paralisis hipokalemia.Kata kunci: periodik paralisis hipokalemia, kelemahan otot, usia 15 tahunAbstract. Periodic paralysis of hypokalemia causes progressive muscle weakness especially in the proximal lower leg muscle groups, acute attacks may occur repeatedly. The first attacks usually occur between the ages of 5 and 35, but the frequency of attacks is highest between the ages of 15 and 35. A case of recurrent hypokalemia periodic paralysis was found in a boy aged 15 years. All the results of clinical symptom analysis and investigations are very supportive for the diagnosis of periodic hypokalemia paralysis. Key words: periodic hypokalemia paralysis, muscle weakness, age 15 years

The Redesign of a Recumbent Tricycle Using a Crank Rocker Mechanism to Increase Power Throughput in FES Cycling

2021 ◽  
Author(s):  
Anthony L. Bazler ◽  
David H. Myszka ◽  
Andrew P. Murray
Keyword(s):  
Electrical Stimulation ◽  
Muscle Contraction ◽  
Functional Electrical Stimulation ◽  
Cardiovascular Health ◽  
Design Criteria ◽  
Muscle Stimulation ◽  
Electrical Currents ◽  
Power Models ◽  
Order Of Magnitude ◽  
A Performance

Abstract This paper presents an investigation of a mechanism to improve the power throughput of persons with tetra- or paraplegia pedaling via functional electrical stimulation (FES). FES stimulates muscle contraction with small electrical currents and has proven useful in building muscle in patients while relieving soreness and promoting cardiovascular health. An FES-stimulated cyclist produces power that is an order of magnitude less than an able-bodied cyclist. At these reduced power levels, many difficulties associated with FES cycling become apparent, namely inactive zones. Inactive zones are defined by the leg being in a position where muscle stimulation is unable to produce power to propel the tricycle forward. A possibility for reducing inactive zones and increasing the power throughput of the cyclist is to alter the motion of a cyclist’s legs. Bicycles have recently been marketed that feature pedaling mechanisms that employ alternate leg motions. This work considers using a four-bar and ratchet-and-pawl linkage in the redesign of a performance tricycle piloted by an FES-stimulated rider. Quasi-static and power models have been optimized for this cycling architecture yielding a design that suggests a 79% increase in throughput power for some FES cyclists. Multiple sets of dimensions are compared against design criteria to identify an ideal design.

scholarly journals Functional Electrical Stimulation for Physiotherapy Management of Neurological Conditions: An Evidence Based Study

2021 ◽  
Vol 6 (3) ◽  
pp. 422-430
Author(s):  
Dhruva J. Kanojiya ◽  
Karishma Jagad
Keyword(s):  
Electrical Stimulation ◽  
Motor Neurons ◽  
Functional Electrical Stimulation ◽  
Gait Training ◽  
Rehabilitation Program ◽  
Foot Drop ◽  
Cord Injury ◽  
Long Time ◽  
Neurological Conditions ◽  
Muscle Groups

Functional Electrical Stimulation is the electrical stimulation of motor neurons such that muscle groups are stimulated to contract & create a moment about a joint. In recent years, FES is relatively used as a new therapeutic tool in rehabilitation program of different neurological conditions. Although FES has been used for long time for treating foot drop, there are many studies which supports the beneficiary effect to improve upper and lower extremity’s function, spasticity, subluxation, respiration, balance, gait training, activities of daily living, quality of life. Multiple databases were searched for relevant articles. The purpose of this study is to evaluate the effectiveness of FES in different neurological condition and to collect the existing literature dealing with FES in a single article to analyze the result & to finally reach the overall conclusion. Keywords: FES, Stroke, Spinal Cord Injury, Multiple Sclerosis, Parkinsonism, etc.

Non-linear analysis of body responses to functional electrical stimulation on hemiplegic subjects

2009 ◽  
Vol 223 (6) ◽  
pp. 653-662 ◽  
Author(s):  
W-W Yu ◽  
U R Acharya ◽  
T-C Lim ◽  
H W Low
Keyword(s):  
Electrical Stimulation ◽  
Functional Electrical Stimulation ◽  
Young Female ◽  
Electrical Currents ◽  
Non Linear ◽  
Linear Signal ◽  
Muscle Groups ◽  
Care Problems ◽  
Signal Processing Methods ◽  
Hemiplegic Gait

Functional electrical stimulation (FES) is a method of applying low-level electrical currents to restore or improve body functions lost through nervous system impairment. FES is applied to peripheral nerves that control specific muscles or muscle groups. Application of advanced signal computing techniques to the medical field has helped to achieve practical solutions to the health care problems accurately. The physiological signals are essentially non-stationary and may contain indicators of current disease, or even warnings about impending diseases. These indicators may be present at all times or may occur at random on the timescale. However, to study and pinpoint these subtle changes in the voluminous data collected over several hours is tedious. These signals, e.g. walking-related accelerometer signals, are not simply linear and involve non-linear contributions. Hence, non-linear signal-processing methods may be useful to extract the hidden complexities of the signal and to aid physicians in their diagnosis. In this work, a young female subject with major neuromuscular dysfunction of the left lower limb, which resulted in an asymmetric hemiplegic gait, participated in a series of FES-assisted walking experiments. Two three-axis accelerometers were attached to her left and right ankles and their corresponding signals were recorded during FES-assisted walking. The accelerometer signals were studied in three directions using the Hurst exponent H, the fractal dimension (FD), the phase space plot, and recurrence plots (RPs). The results showed that the H and FD values increase with increasing FES, indicating more synchronized variability due to FES for the left leg (paralysed leg). However, the variation in the normal right leg is more chaotic on FES.

Motorized and Functional Electrical Stimulation Induced Cycling via Switched Adaptive Concurrent Learning Control

2020 ◽  
Author(s):  
Jonathan Casas ◽  
Chen-Hao Chang ◽  
Victor H. Duenas
Keyword(s):  
Electrical Stimulation ◽  
Functional Electrical Stimulation ◽  
Adaptive Systems ◽  
Adaptive Controller ◽  
Adaptive Method ◽  
Second Phase ◽  
Excitation Condition ◽  
Concurrent Learning ◽  
Cycle System ◽  
Muscle Groups

Abstract Cycling induced by functional electrical stimulation (FES) with motorized assistance is a rehabilitative approach for individuals with movement impairments. In this paper, an adaptive controller is designed for cadence tracking by switching across multiple muscle groups and an electric motor. The control design and analysis are based on a recently developed adaptive method called integral concurrent learning and an invariance-like tool to ensure stability of switched adaptive systems. A Lyapunov-based stability analysis for the overall switched rider-cycle system is segregated into two phases. During the first phase when sufficient learning has not been attained, which is quantified by a finite excitation condition, global asymptotic tracking and bounded parameter estimation are guaranteed. In the second phase, global exponential tracking and parameter convergence is ensured after the finite excitation condition is satisfied for all the subsystems within a finite time.

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