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Development of Rehabilitation Applications by Using Wearable Sensors

Development of Rehabilitation Applications by Using Wearable Sensors
Translated Title
착용 가능한 센서를 사용한 재활 어플리케이션 개발
Jeon, Sang Hoon
DGIST Authors
Jeon, Sang Hoon; Son, Sang Hyuk; Park, Tae Joon
Son, Sang Hyuk; Park, Tae Joon
Kim, Il Kon
Issue Date
Available Date
Degree Date
2014. 2
Rehabilitation applicationsin-sleep strokeSEMG pattern recognitionco-contraction EMG재활 어플리케이션수면중 뇌졸중표면 근전도의 패턴인식동시 수축 근전도
As aging population becomes a major issue in a number of countries, more medical services are increased. Wearable sensor will substitute for the role of healthcare providers to accommodate increasing requirements of rehabilitation which has characteristics of labor- intensive and time-consuming. We chose two wearable sensors such as 6 degree of freedom inertial measurement unit (6-DOF IMU) and surface electromyography (SEMG) sensor, and proposed rehabilitation applications related to early detection of disorders and home rehabilitation. First, we proposed a novel system for monitoring in-sleep stroke by detecting abnormal activity ratio of the left and right arms from wearable the 6-DOF IMU sensor which consists of an accelerometer and gyroscope sensor. We extracted multiple features for consists of an accelerometer and gyroscope sensor. We extracted multiple features for and detected stroke by sliding window method with stroke thresholds according to the each feature. The system discriminated stroke 75.48% by the accelerometer sensor and 97.12% by the gyroscope sensor in sleep data of the stroke patients with hemiparesis. Second, we tested a feasibility of the SEMG pattern recognition for training of activity daily life. We experimented from simple motions to complicated motions considering variables such as time, electrode position and person change. The results showed that the SEMG pattern recognition is largely influenced by the three variables because of structural problems in the muscle and the SEMG sensor. We concluded that the SEMG is appropriate in simple application such as co-contraction EMG detecting whether a muscle is activated. ⓒ 2014 DGIST
Table Of Contents
I. Introduction 1 -- II. Background – Current Wearable Sensor Technology 3 -- III. Stroke Detection by Accelerometer and Gyroscope 5 -- 3.1 Introduction 5 -- 3.2 Background 6 -- 3.2.1 Stroke 6 -- 3.2.2 Accelerometer 7 -- 3.2.3 Gyroscope 8 -- 3.2.4 Receiver Operating Characteristic (ROC) Curve 9 -- 3.3 Proposed Approach for Early Detection of In-sleep Stroke 11 -- 3.4 Results 16 -- 3.5 Conclusion and Discussion 23 -- IV. Feasibility study of Surface EMG sensor 25 -- 4.1 Introduction 25 -- 4.2 Background 26 -- 4.2.1 Muscle Anatomy 26 -- 4.2.2 Surface EMG 28 -- 4.3 Method 29 -- 4.3.1 SEMG Sensor 29 -- 4.3.2 Evaluation Method 30 -- 4.3.3 Evaluation Items 30 -- 4.3.4 Evaluation Method 31 -- 4.4 Experimental Results 32 -- 4.4.1 Simple Motion test 32 -- 4.4.2 Complicated Motion test 33 -- 4.5 Conclusion and Discussion 37 -- V. Conclusion and Future work 39 -- References 41 -- 요약문 44
Information and Communication Engineering
Information and Communication EngineeringThesesMaster

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