Development of a wearable activity tracker based on BBC micro:bit and its performance analysis for detecting bachata dance steps
Kemal Avcı · Scientific Reports · 2024
The rising popularity of wearable activity tracking devices can be attributed to their capacity for gathering and analysing ambient data, which finds utility across numerous applications. In this study, a wearable activity tracking device is developed using the BBC micro:bit development board to identify basic bachata dance steps. Initially, a pair of smart ankle bracelets is crafted, employing the BBC micro:bit board equipped with a built-in accelerometer sensor and a Bluetooth module for transmitting accelerometer data to smartphones. Subsequently, a dataset encompassing six core bachata dance steps synchronized to four beats is created from ten participants to examine the performance of the system. A metric using squared Euclidean distance is applied for the accelerometer raw data to facilitate and standardize the automatic detection of the steps by the system. A user interface, built with Python and Tkinter library, is developed to enable automatic step detection using the accelerometer dataset. The results demonstrated a system accuracy rate of 79.2%.