Foot Position Recognition Using a Smartphone Inertial Sensor in Patient Transfer

Abstract

Caregivers experience lower back pain due to patient transfer. Foot position is an important and adjustable posture for reducing lumbar loads during patient transfer. Specifically, a suitable foot position provides the use of the lower limbs instead of the lumbar region in patient handling. Thus, we have developed a monitoring and feedback system for foot positioning using wearable sensors to instruct suitable foot positions. However, existing measurement methods require multiple specific wearable sensors. In addition, the existing method has not been evaluated in patient transfer, including twisting and lowering. Thus, the objective of this study was to develop and evaluate a measurement method using only a smartphone-installed inertial sensor for foot position during patient transfer, including twisting and lowering. The smartphone attached to the trunk measures the acceleration, angular velocity, and geomagnetic field. The proposed method recognizes anteroposterior and mediolateral foot positions by machine learning using inertial data. The proposed method was tested using simulated patient transfer motions, including horizontal rotation. The results showed that the proposed method could recognize the two foot positions with more than 90% accuracy. These results indicate that the proposed method can be applied to wearable monitoring and feedback systems to prevent lower back pain caused by patient transfer.