Applying EMG technology in medial and lateral elbow enthesopathy treatment using Myo motion controller

被引:6
作者
Grabczynski, Adam [1 ]
Szklanny, Krzysztof [1 ]
Wrzeciono, Piotr [2 ]
机构
[1] Polish Japanese Acad Informat Technol, Multimedia Dept, Warsaw, Poland
[2] Warsaw Univ Life Sci, SGGW, Fac Appl Informat & Math, Warsaw, Poland
关键词
Myo movement controller; Electromyography; Tennis elbow; Rehabilitation; REAL-TIME; ELECTROMYOGRAPHY; CLASSIFICATION; EPICONDYLITIS; PREVALENCE;
D O I
10.1007/s13246-019-00770-5
中图分类号
R318 [生物医学工程];
学科分类号
100103 [病原生物学];
摘要
Electromyography (EMG) is a diagnostic technique allowing for the detection of signals generated by changes in electrical potentials of striated muscles. The application of this technology is becoming an increasingly popular subject of scientific research. With the appearance of new devices retrieving EMG data, novel methods of its processing for various purposes are being developed. One such device is the Myo movement controller, produced by Thalmic Labs (now North). The device has been used for the analysis of muscle activation levels in patients with "tennis elbow" and "golfer's elbow"-conditions of upper limbs which usually result from occupational injuries. The process of their rehabilitation is complex and requires a continuous monitoring of its progress. The data obtained by means of the Myo controller was used for pattern recognition of an injured hand with relation to the healthy one. The study involved examining ten subjects, including five controls. The results indicate that the muscle activation force is considerably lower in injured individuals. The arithmetic mean for the 6 analyzed motions in the injured group is 38.54% lower. The SmartEMG application () enables the implementation of procedures performed during an examination as well as those involved in the management of the collected recordings. The study produced satisfactory results, which indicates the possibility of using the Myo controller in the treatment of elbow enthesopathy.
引用
收藏
页码:701 / 710
页数:10
相关论文
共 35 条
[1]
Evaluating Sign Language Recognition Using the Myo Armband [J].
Abreu, Joao Gabriel ;
Teixeira, Joao Marcelo ;
Figueiredo, Lucas Silva ;
Teichrieb, Veronica .
2016 18TH SYMPOSIUM ON VIRTUAL AND AUGMENTED REALITY (SVR 2016), 2016, :64-70
[2]
Akhmadeev K, 2017, ENOC 2017, V2017
[3]
[Anonymous], 2016, 2016 8 INT C COMM SY
[4]
[Anonymous], 2006, ENCY MED DEVICES INS
[5]
[Anonymous], SERBIAN J ELECT ENG
[6]
Spectral Collaborative Representation based Classification for hand gestures recognition on electromyography signals [J].
Boyali, Ali ;
Hashimoto, Naohisa .
BIOMEDICAL SIGNAL PROCESSING AND CONTROL, 2016, 24 :11-18
[7]
Cacioppo JT, 2007, HANDBOOK OF PSYCHOPHYSIOLOGY, 3RD EDITION, P1, DOI 10.2277/ 0521844711
[8]
Effect of Lateral Epicondylosis on Grip Force Development [J].
Chourasia, Amrish O. ;
Buhr, Kevin A. ;
Rabago, David P. ;
Kijowski, Richard ;
Irwin, Curtis B. ;
Sesto, Mary E. .
JOURNAL OF HAND THERAPY, 2012, 25 (01) :27-37
[9]
Influence of 50 Hz-1 mT magnetic field on human median nerve [J].
Comlekci, Selcuk ;
Coskun, Ozlem .
ELECTROMAGNETIC BIOLOGY AND MEDICINE, 2012, 31 (04) :285-292
[10]
Disselhorst-Klug, 2012, EMG METHODS EVALUATI, P227