Wrist Rehabilitation Robot System and Its Effectiveness for Patients

Yamamoto, Ikuo; Matsui, Miki; Higashi, Toshio; Iso, Nozomi; Hachisuka, Kenji; Hachisuka, Akiko

doi:10.18494/sam.2018.1901

Cited by 10 publications

(4 citation statements)

References 10 publications

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“…In that context, comprehending physical weariness has developed into a topic of intense scientific interest because of its significance for obtaining successful recovery [13]. Numerous articles were published over the past 20 years that suggested that modeling techniques and characteristics extract useful data from EMG [14][15][16][17][18][19][20][21][22]. In [14], a new concept for a lightweight exoskeleton rehabilitation robot controlled by surface electromyography was presented for at-home progressive resistance training.…”

Section: Introductionmentioning

confidence: 99%

A New Wrist–Forearm Rehabilitation Protocol Integrating Human Biomechanics and SVM-Based Machine Learning for Muscle Fatigue Estimation

2023

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In this research, a new remote rehabilitation system was developed that integrates an IoT-based connected robot intended for wrist and forearm rehabilitation. In fact, the mathematical model of the wrist and forearm joints was developed and integrated into the main controller. The proposed new rehabilitation protocol consists of three main sessions: the first is dedicated to the extraction of the passive components of the dynamic model of wrist–forearm biomechanics while the active components are extracted in the second session. The third session consists of performing continuous exercises using the determined dynamic model of the forearm–wrist joints, taking into account the torque generated by muscle fatigue. The main objective of this protocol is to determine the state level of the affected wrist and above all to provide a dynamic model in which the torque generated by the robot and the torque supplied by the patient are combined, taking into account the constraints of fatigue. A Support Vector Machine (SVM) classifier is designed for the estimation of muscle fatigue based on the features extracted from the electromyography (EMG) signal acquired from the patient. The results show that the developed rehabilitation system allows a good progression of the joint’s range of motion as well as the resistive-active torques.

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Section: Introductionmentioning

confidence: 99%

A New Wrist–Forearm Rehabilitation Protocol Integrating Human Biomechanics and SVM-Based Machine Learning for Muscle Fatigue Estimation

2023

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“…Table (5) shows the resulting range of motions and velocity information for the exoskeleton. Figures (16)(17)(18)(19)(20)(21) show the movements of the exoskeleton in addition to their corresponding curves denoting the reflected range of motions and velocities respectively. Figures.…”

Section: Resultsmentioning

confidence: 99%

“…As a result, many researchers have been interested in this field in which they developed and introduce new rehabilitation devices aiming to override the problems as much as possible [16][17][18]. However, the proposed devices still need several enhancements and reinforcements in terms of the technology usage in the implementation and manufacturing of them, the number of degree of freedom that shows by the considered device required to rehabilitate the defected limb to its optimum level, their restricted mode of operations which reflect on the efficiency of the rehabilitation process, their limitations to concerned on specific defected cases.…”

Section: Introductionmentioning

confidence: 99%

Robotic Exoskeleton: A Compact, Portable, and Constructing Using 3D Printer Technique for Wrist-Forearm Rehabilitation

Shalal

Aboud

2020

NJES

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Regaining the activities of daily living after stroke and spinal cord injury requires repetitive and intensive tasks, meaning that rehabilitation therapy should be treated with a long duration. Thus, the need for rehabilitation devices based home is of most importance to increase the rehabilitation process and provide more comfortability for patients. This paper focuses on implementing and construction of a three degree of freedom (DOF) (flexion/extension, adduction/abduction, and pronation/supination), low cost, lightweight, and portable robotic exoskeleton for wrist-forearm rehabilitation. SolidWorks software program and 3D printer technology are used to model and construct the proposed robotic exoskeleton structure. In addition, the anthropometric parameters of the normal human lower arm are considered for this exoskeleton to provide a range of motion (ROM) and velocity for the links, joints, which matches with the anatomical structure of human and also to avoid the excesses motions over the normal range. The exoskeleton is constructed by a 3D printer utilizing polylactic acid (PLA) plastic material. The proposed implementing structure of the robotic exoskeleton shows comfortable, lightweight, simple and economic as well.

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“…Compared to [14,[23][24][25][26], the developed system is a vision-based telemanipulation solution that avoids the inconveniences of the EMG-based solutions, such as signal sensitivity. Many studies on robotic rehabilitation have not taken into account the pain felt by the patient in the robot control architecture; see [38][39][40][41][42], to name a few. However, this pain can prevent a person from interacting positively with therapy.…”

Section: Introductionmentioning

confidence: 99%

Development of an IoT-Based Solution Incorporating Biofeedback and Fuzzy Logic Control for Elbow Rehabilitation

et al. 2020

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The last few years have seen significant advances in neuromotor rehabilitation technologies, such as robotics and virtual reality. Rehabilitation robotics primarily focuses on devices, control strategies, scenarios and protocols aimed at recovering sensory, motor and cognitive impairments often experienced by stroke victims. Remote rehabilitation can be adopted to relieve stress in healthcare facilities by limiting the movement of patients to clinics, mainly in the current COVID-19 pandemic. In this context, we have developed a remote controlled intelligent robot for elbow rehabilitation. The proposed system offers real-time monitoring and ultimately provides an electronic health record (EHR). Rehabilitation is an area of medical practice that treats patients with pain. However, this pain can prevent a person from positively interacting with therapy. To cope with this matter, the proposed solution incorporates a cascading fuzzy decision system to estimate patient pain. Indeed, as a safety measure, when the pain exceeds a certain threshold, the robot must stop the action even if the desired angle has not yet been reached. A fusion of sensors incorporating an electromyography (EMG) signal, feedback from the current sensor and feedback from the position encoder provides the fuzzy controller with the data needed to estimate pain. This measured pain is fed back into the control loop and processed to generate safe robot actions. The main contribution was to integrate vision-based gesture control, a cascade fuzzy logic-based decision system and IoT (Internet of Things) to help therapists remotely take care of patients efficiently and reliably. Tests carried out on three different subjects showed encouraging results.

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Wrist Rehabilitation Robot System and Its Effectiveness for Patients

Cited by 10 publications

References 10 publications

A New Wrist–Forearm Rehabilitation Protocol Integrating Human Biomechanics and SVM-Based Machine Learning for Muscle Fatigue Estimation

A New Wrist–Forearm Rehabilitation Protocol Integrating Human Biomechanics and SVM-Based Machine Learning for Muscle Fatigue Estimation

Robotic Exoskeleton: A Compact, Portable, and Constructing Using 3D Printer Technique for Wrist-Forearm Rehabilitation

Development of an IoT-Based Solution Incorporating Biofeedback and Fuzzy Logic Control for Elbow Rehabilitation

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