Open AccessMeasurement Method for Erector Spinae Muscle Activity during Patient Handling Using Inertial Sensor and Shoe-type Force Sensor
Author(s) -
Kodai Kitagawa,
Koji Matsumoto,
Kensuke Iwanaga,
Siti Anom Ahmad,
Takayuki Nagasaki,
Satoshi Nakano,
M. Hida,
Shogo Okamatsu,
Chikamune Wada
Publication year - 2021
Publication title -
international journal of electrical and electronic engineering and telecommunications
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.171
H-Index - 6
ISSN - 2319-2518
DOI - 10.18178/ijeetc.10.4.283-287
Subject(s) - erector spinae muscles , lumbar , electromyography , accelerometer , muscle fatigue , physical medicine and rehabilitation , back muscles , low back pain , inertial frame of reference , biomedical engineering , simulation , computer science , medicine , anatomy , physics , alternative medicine , pathology , quantum mechanics , operating system
Because caregivers often experience lower back pain caused by lumbar load from patient handling, monitoring this load can help prevent pain. Erector spinae muscle activity, which is measured and monitored as lumbar load, is commonly measured by electromyography (EMG). However, EMG’s electrodes can cause skin irritation and be uncomfortable. Therefore, measuring muscle activity without electrodes is necessary. In this study, we propose a method for estimating erector spinae muscle activity using wearable sensors, specifically inertial and shoe-type force sensors. Inertial sensors measure acceleration and angular velocity of the trunk. Shoe-type force sensors measure vertical force of the feet. A regression model obtained from a machine learning algorithm can predict erector spinae muscle activity using inertial and force data. In our experiment, we evaluated the accuracy of our method by comparing sensor data with surface EMG data in patient handling. Results show that this method can measure erector spinae muscle activity with a small error (less than 5% maximal voluntary contractions) and a significantly high correlation with actual value (r = 0.891, p <0.05). In addition, a Bland-Altman plot showed no fixed and proportional errors. These findings indicate that our proposed method can accurately monitor the lumbar loads of caregivers.