Monitoring muscle fatigue following continuous load changes

Department of Human Factors EngineeringPrevious studies related to monitoring muscle fatigue during dynamic motion have focused on detecting the accumulation of muscle fatigue. However, it is necessary to detect both accumulation and recovery of muscle fatigue in dynamic muscle contraction while muscle load changes continuously. This study aims to investigate the development and recovery of muscle fatigue in dynamic muscle contraction conditions following continuous load changes. Twenty healthy males conducted repetitive elbow flexion and extension using 2kg and 1kg dumbbell, by turns. They performed the two tasks of different intensity (2kg intensity task, 1kg intensity task) alternately until they felt they could no longer achieve the required movement range or until they experienced unacceptable biceps muscle discomfort. Meanwhile, using EMG signal of biceps brachii muscle, fatigue detections were performed from both dynamic measurements during each dynamic muscle contraction task and isometric measurements during isometric muscle contraction right before and after each task. In each of 2kg and 1kg intensity tasks, pre, post and change value of EMG amplitude (AEMG) and center frequency were computed respectively. They were compared to check the validity of the muscle fatigue monitoring method using Wavelet transform with EMG signal from dynamic measurements. As a result, a decrease of center frequency in 2kg intensity tasks and an increase of center frequency in 1kg intensity tasks were detected. It shows that development and recovery of muscle fatigue were detected in 2kg and 1kg intensity tasks, respectively. Also, the tendency of change value of center frequency from dynamic measurements were corresponded with that from isometric measurements. It suggests that monitoring muscle fatigue in dynamic muscle contraction conditions using wavelet transform was valid to detect the development and recovery of muscle fatigue continuously. The result also shows the possibility of monitoring muscle fatigue in real-time in industry and it could propose a guideline in designing a human-robot interaction system based on monitoring user's muscle fatigue.clos

Functional Electrical Stimulation mediated by Iterative Learning Control and 3D robotics reduces motor impairment in chronic stroke

Background: Novel stroke rehabilitation techniques that employ electrical stimulation (ES) and robotic technologies are effective in reducing upper limb impairments. ES is most effective when it is applied to support the patients’ voluntary effort; however, current systems fail to fully exploit this connection. This study builds on previous work using advanced ES controllers, and aims to investigate the feasibility of Stimulation Assistance through Iterative Learning (SAIL), a novel upper limb stroke rehabilitation system which utilises robotic support, ES, and voluntary effort. Methods: Five hemiparetic, chronic stroke participants with impaired upper limb function attended 18, 1 hour intervention sessions. Participants completed virtual reality tracking tasks whereby they moved their impaired arm to follow a slowly moving sphere along a specified trajectory. To do this, the participants’ arm was supported by a robot. ES, mediated by advanced iterative learning control (ILC) algorithms, was applied to the triceps and anterior deltoid muscles. Each movement was repeated 6 times and ILC adjusted the amount of stimulation applied on each trial to improve accuracy and maximise voluntary effort. Participants completed clinical assessments (Fugl-Meyer, Action Research Arm Test) at baseline and post-intervention, as well as unassisted tracking tasks at the beginning and end of each intervention session. Data were analysed using t-tests and linear regression. Results: From baseline to post-intervention, Fugl-Meyer scores improved, assisted and unassisted tracking performance improved, and the amount of ES required to assist tracking reduced. Conclusions: The concept of minimising support from ES using ILC algorithms was demonstrated. The positive results are promising with respect to reducing upper limb impairments following stroke, however, a larger study is required to confirm this

Coupling Robot-aided assessment and surface electromyography to evaluate wrist and forearm muscles activity, muscle fatigue and its effect on proprioception

Sensorimotor functions and an intact neural control of muscles are essential for the effective execution of movements during daily living tasks. However, despite the ability of human sensorimotor system to cope with a great diversity of internal and external demands and constraints, these mechanisms can be altered as a consequence of neurological disorders, injuries or just due to excessive effort leading to muscle fatigue. A precise assessment of both motor and sensory impairment is thus needed in order to provide useful cues to monitor the progression of the disease in pathological populations or to prevent injuries in case of workers. In particular, considering muscle fatigue, an objective assessment of its manifestation may be crucial when dealing with subjects with neuromuscular disorders for understanding how specific disease features evolve over time or for testing the efficacy of a potential therapeutic strategy. Indeed, muscle fatigue accounts for a significant portion of the disease burden in populations with neuromuscular diseases but, despite its importance, a standardized, reliable and objective method for fatigue measurement is lacking in clinical practice. The work presented in this thesis investigates a practical solution through the use of a robotic task and parameters extracted by surface electromyography signals. Moreover, a similar approach that combines robot-mediated proprioception test and muscle fatigue assessment has been developed and used in this thesis to objectively investigate the influence of muscle fatigue on position sense. Finally, the effect of posture on muscle activity, from a perspective of injuries prevention, has been examined. Data on adults and children have been collected and quantitative and objective information about muscle activity, muscle fatigue and joint sensitivity were obtained gaining useful insight both in the clinical context and in the prevention of workplace injuries. A novel method to assess muscle fatigue has been proposed together with the definition of an easy readable indicator that can help clinicians in the assessment of the patient. As for the impact of fatigue on the sensorimotor system, results obtained showed a decrease in wrist proprioceptive acuity which led also to a decline in the performance of a simple tracing task. Regarding the adoption of different muscle strategies depending on postures, results showed that muscle activity of forearm muscles was overall similar regardless from the postures

Aerospace Medicine and Biology. A continuing bibliography (Supplement 226)

This bibliography lists 129 reports, articles, and other documents introduced into the NASA scientific and technical information system in November 1981

Exploration of muscle fatigue effects in bioinspired robot learning from sEMG signals

© 2018 Ning Wang et al. To investigate the effects of muscle fatigue on bioinspired robot learning quality in teaching by demonstration (TbD) tasks, in this work, we propose to first identify the emerging muscle fatigue phenomenon of the human demonstrator by analyzing his/her surface Electromyography (sEMG) recordings and then guide the robot learning curve with this knowledge in mind. The time-varying amplitude and frequency sequences determining the subband sEMG signals have been estimated and their dominant values over short time intervals have been explored as fatigue-indicating features. These features are found carrying muscle fatigue cues of the human demonstrator in the course of robot manipulation. In robot learning tasks requiring multiple demonstrations, the fatiguing status of human demonstrator can be acquired by tracking the changes of the proposed features over time. In order to model data from multiple demonstrations, Gaussian mixture models (GMMs) have been employed. According to the identified muscle fatigue factor, a weight has been assigned to each of the demonstration trials in training stage, which is therefore termed as weighted GMMs (W-GMMs) algorithm. Six groups of data with various fatiguing status, as well as their corresponding weights, are taken as input data to get the adapted W-GMMs parameters. After that, Gaussian mixture regression (GMR) algorithm has been applied to regenerate the movement trajectory for the robot. TbD experiments on Baxter robot with 30 human demonstration trials show that the robot can successfully accomplish the taught task with a generated trajectory much closer to that of the desirable condition where little fatigue exists

The re-education of upper limb movement post stroke using iterative learning control mediated by electrical stimulation

An inability to perform tasks involving reaching is a common problem following stroke. Evidence supports the use of robotic therapy and electrical stimulation (ES) to reduce upper limb impairments following stroke, but current systems may not encourage maximal voluntary contribution from the participant. This study developed and tested iterative learning control (ILC) algorithms mediated by ES, using a purpose designed robotic workstation, for upper limb rehabilitation post stroke. Surface electromyography (EMG) which may be related to impaired performance and function was used to investigate seven shoulder and elbow muscle activation patterns in eight neurologically intact and five chronic stroke participants during nine tracking tasks. The participants’ forearm was supported using a hinged arm-holder, which constrained their hand to move in a two dimensional horizontal plane.Outcome measures taken prior to and after an intervention consisted of the Fugl-Meyer Assessment (FMA) and the Action Research Arm Test (ARAT), isometric force and error tracking. The intervention for stroke participants consisted of eighteen sessions in which a similar range of tracking tasks were performed with the addition of responsive electrical stimulation to their triceps muscle. A question set was developed to understand participants’ perceptions of the ILC system. Statistically significant improvements were measured (p?0.05) in: FMA motor score, unassisted tracking, and in isometric force. Statistically significant differences in muscle activation patterns were observed between stroke and neurologically intact participants for timing, amplitude and coactivation patterns. After the intervention significant changes were observed in many of these towards neurologically intact ranges. The robot–assisted therapy was well accepted and tolerated by the stroke participants. This study has demonstrated the feasibility of using ILC mediated by ES for upper limb stroke rehabilitation in the treatment of stroke patients with upper limb hemiplegia

Aerospace medicine and biology: A continuing bibliography with indexes (supplement 359)

This bibliography lists 164 reports, articles and other documents introduced into the NASA Scientific and Technical Information System during Jan. 1992. Subject coverage includes: aerospace medicine and physiology, life support systems and man/system technology, protective clothing, exobiology and extraterrestrial life, planetary biology, and flight crew behavior and performance

An adaptive 4-week robotic training program of the upper limb for persons with multiple sclerosis

It is suggested that repetitive movements can initiate motor recovery and improve motor learning in populations with neurological impairments and this process can be optimized with robotic devices. The repetitive, reproducible and high dose motor movements that can be delivered by robotics have shown positive results in functional outcomes in stroke patients. However, there is little research on robotic neurorehabilitation for persons with multiple sclerosis (PwMS), more specifically there is lack of literature with focus on the upper extremity. Therefore, the purpose of this work was to use a robotic device to implement an adaptive training program of the forearm and wrist for PwMS. This approach is unique, as it incorporates real time learning from the robotic device to alter the level of assistance/resistance to the individual. This methodology is novel and could prove to be an effective way to properly individualize the therapy process with correct dosage and prescription. 7 individuals with varying levels of MS, placed their most affected limb (forearm) on a robotic device (Wristbot), grasped the handle, and using real-time visual feedback, traced a Lissajous curve allowing the wrist to move in flexion/extension, radial/ulnar directions. Robotic training occurred 3 times per week for 4 consecutive weeks and included 40 minutes of work. Robotic software was adaptive and updated every 3 laps to evaluate the average kinematic performance which modified the robotic assistance/resistance. Outcome measures were taken pre and post intervention. Improvements in performance were quantified by average tracking and figural error, which was significantly reduced from pre – post intervention. Isometric wrist strength and grip force endurance also significantly improved from pre to post intervention. However, maximum grip force, joint position matching, 9-hole peg test, and patient-rated wrist evaluation did not show any significant improvements. To our knowledge, this study was the first adaptive and individualized robotic rehabilitation program providing two opposing forces to the hand/wrist for PwMS. Results of this 4-week training intervention, provide a proof-of-concept that motor control and muscular strength can be improved by this rehabilitation modality. This work acts as a stepping-stone into future investigations of robotic rehabilitation for an MS population

Aerospace medicine and biology: A continuing bibliography with indexes (supplement 324)

This bibliography lists 200 reports, articles and other documents introduced into the NASA Scientific and Technical Information System during May, 1989. Subject coverage includes: aerospace medicine and psychology, life support systems and controlled environments, safety equipment, exobiology and extraterrestrial life, and flight crew behavior and performance