Developing a smart walking cane with remote electrocardiogram and fall detection

Abstract

This study developed a smart cane with remote electrocardiogram (ECG) and fall detection. The cane comprises a self-developed ECG detection circuit, fall detection module composed of a three-axis gyroscope and three-axis accelerator, and two wireless transmission modules. The data reception end features a human–machine interface with self-developed ECG analysis and fall detection programs, providing reference data for identifying an abnormal situation. The hardware of the proposed system is divided into two parts. First, ECG detection is achieved using a copper column-shaped detector in place of conventional ECG electrodes. The self-developed sensor circuit amplifies the collected signals and filters unwanted noise to generate complete ECG signals. An Arduino MEGA microcontroller board and the two wireless transmission modules then transmit the signals to the human–machine interface. Second, fall detection is achieved using the aforementioned fall detection module to collect numerical data, which are then transmitted to the human–machine interface through the Arduino MEGA and wireless transmission modules. The proposed system can be applied to real-time monitoring and provide reference data for health care professionals and nursing personnel.