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Erschienen in:
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2019 | OriginalPaper | Buchkapitel

Classification of the Shoulder Movements for Intelligent Frozen Shoulder Rehabilitation

verfasst von : Shweta, Padmavati Khandnor, Neelesh Kumar, Ratan Das

Erschienen in: Smart Innovations in Communication and Computational Sciences

Verlag: Springer Singapore

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Abstract

Frozen shoulder is a medical condition leading to stiffness in the shoulder joint and also restricting the range of motion of the shoulder joint. The paper compiles the details about the four basic movements of the shoulder joint, namely the flexion/extension, abduction/adduction, internal rotation and external rotation movements. Shoulder movements of 150 subjects were recorded, and the data was further analyzed and classified using the K-nearest neighbor algorithm, support vector machine, and also using logistic regression algorithm. The data is recorded using a module consisting of a triaxial accelerometer, a HC-05 Bluetooth module and triaxial gyroscope. SVM shows an accuracy of approximately 99.99% over the classification of the four shoulder movements and is proved to be better than other classifiers. Classification of the shoulder movements can be further used to classify an individual as either a patient suffering from frozen shoulder or a normal individual.

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Metadaten
Titel
Classification of the Shoulder Movements for Intelligent Frozen Shoulder Rehabilitation
verfasst von
Shweta
Padmavati Khandnor
Neelesh Kumar
Ratan Das
Copyright-Jahr
2019
Verlag
Springer Singapore
Buch
Smart Innovations in Communication and Computational Sciences

Print ISBN: 978-981-10-8970-1

Electronic ISBN: 978-981-10-8971-8

Copyright-Jahr: 2019

DOI
https://doi.org/10.1007/978-981-10-8971-8_1