A Body Sensor Network With Electromyogram and Inertial Sensors: Multimodal Interpretation of Muscular Activities

Abstract

The evaluation of the postural control system (PCS) has applications in rehabilitation, sports medicine, gait analysis, fall detection, and diagnosis of many diseases associated with a reduction in balance ability. Standing involves significant muscle use to maintain balance, making standing balance a good indicator of the health of the PCS. Inertial sensor systems have been used to quantify standing balance by assessing displacement of the center of mass, resulting in several standardized measures. Electromyogram (EMG) sensors directly measure the muscle control signals. Despite strong evidence of the potential of muscle activity for balance evaluation, less study has been done on extracting unique features from EMG data that express balance abnormalities. In this paper, we present machine learning and statistical techniques to extract parameters from EMG sensors placed on the tibialis anterior and gastrocnemius muscles, which show a strong correlation to the standard parameters extracted from accelerometer data. This novel interpretation of the neuromuscular system provides a unique method of assessing human balance based on EMG signals. In order to verify the effectiveness of the introduced features in measuring postural sway, we conduct several classification tests that operate on the EMG features and predict significance of different balance measures.

Evaluation of Cervical Posture Improvement of Children with Cerebral Palsy After Physical Therapy with a HCI Based on Head Movements and Serious Videogames

“…Motion sensing, by means of MEMS inertial sensors a real scientific breakthrough in the medical field, where there is a need for small ambulatory sensor systems for measuring the kinematics of body segments [17]. As a result, inertial sensors have been chosen for different applications focused on people with motor disorders, such as the evaluation of clinical spasticity assessment (by measuring the range of motion) [18] and the quantification of standing balance by assessing displacement of the center of mass in CP [19] and clinical assessment of tremor in Parkinson [20]. …”

Sensor Deployments for Home and Community Settings

“…Body-worn sensors (BWS) have been used in a wide variety of physiological and kinematic monitoring applications (Catherwood et al, 2010, Ghasemzadeh et al, 2010, Aziz et al, 2006. BWS have the potential to support the clinical judgment of community-based practitioners through the provision of objective measures for tests, which are currently administered in a qualitative manner.…”

Biomedical sensor technologies on the platform of mobile phones

“…Actually, wireless sensing has been successfully employed in a variety of applications including environmental monitoring, structural monitoring, and surveillance, and applying this to clinical environment especially for patients or people with chronic conditions, such as hypertension, diabetes, or sleep apnea is in need. Ever since, more and more people have come to research or construct this network to improve people's healthcare and assisting their life [35][36][37][38][39][40][41][42][43][44][45][46][47][48][49][50][51].…”