Abstract
Secondary injuries are common during upper limb rehabilitation training because of uncontrollable physical force and overexciting activities, and long-time training may cause fatigue and reduce the training effect. This study proposes a wearable monitoring device for upper limb rehabilitation by integrating electrocardiogram and electromyogram (ECG/EMG) sensors and using data acquisition boards to obtain accurate signals during robotic glove assisting training. The collected ECG/EMG signals were filtered, amplified, digitized, and then transmitted to a remote receiver (smart phone or laptop) via a low-energy Bluetooth module. A software platform was developed for data analysis to visualize ECG/EMG information, and integrated into the robotic glove control module. In the training progress, various hand activities (i.e., hand closing, forearm pronation, finger flexion, and wrist extension) were monitored by the EMG sensor, and the changes in the physiological status of people (from excited to fatigue) were monitored by the ECG sensor. The functionality and feasibility of the developed physiological monitoring system was demonstrated by the assisting robotic glove with an adaptive strategy for upper limb rehabilitation training improvement. The feasible results provided a novel technique to monitor individual ECG and EMG information holistically and practically, and a technical reference to improve upper limb rehabilitation according to specific treatment conditions and the users’ demands. On the basis of this wearable monitoring system prototype for upper limb rehabilitation, many ECG-/EMG-based mobile healthcare applications could be built avoiding some complicated implementation issues such as sensors management and feature extraction.
Highlights
Wearable devices usually involve smart sensors to detect various parameters of the human body and remind the wearer or caregiver to take appropriate action [1,2]
This study demonstrates a newly developed wearable physiological monitoring system which integrated the electrocardiogram and electromyogram (ECG/EMG) sensors and the DAQ boards to obtain accurate physiological signals during upper limb rehabilitation training
A robotic glove was adopted as an applied example of the developed system to assist upper limb rehabilitation training, and the commonly adopted hand activities were monitored using EMG sensors, while the physiological status of people was detected by the ECG sensor
Summary
Wearable devices usually involve smart sensors to detect various parameters of the human body and remind the wearer or caregiver to take appropriate action [1,2]. With the advances in mobile technology and the great demand of the aging population for healthcare management, the emergence of wearable medical devices enables people to monitor their personal health information in real time [3,4,5]. ECG and EMG, which are caused by electrical signal variations during muscular activities, are important and commonly adopted parameters for healthcare management. The slight electrical variation on the skin is produced by the electrophysiologic pattern (i.e., depolarizing and repolarizing) of the heart muscle during each heartbeat and detected using the ECG signal detection system. With the increased awareness of people’s health and the continuous development of science and technology, the ECG signal detection system is developed in the direction of miniaturization, family, and intelligence.
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