ALGORITHMIC DESIGN AND SOFTWARE FOR A MICROCONTROLLER-BASED WEARABLE BIOMEDICAL SENSOR MONITORING SYSTEM VIA ESP-NOW PROTOCOL
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Abstract
This paper presents a hardware-software implementation of a microprocessor-based distributed system for monitoring human motion biomechanics using wireless communication for real-time data transmission. The main objective of the work is to develop an energy-efficient, reliable, and low-cost system capable of autonomously collecting, transmitting, synchronizing, and storing data from inertial sensors in real time. The proposed approach is based on the use of ESP32 microcontrollers, which support direct data exchange via the ESP-NOW protocol. This protocol enables high-speed, low-latency data communication without connection establishment, ensuring fast response and reduced power consumption. A functional system prototype has been developed, consisting of a base station and a set of sensor modules powered by standalone battery sources. The study introduces a specialized algorithm for synchronized data transmission, which includes packetization of inertial measurement unit (IMU) readings and data caching using a circular buffer. This significantly reduces packet loss even under interference and high channel load conditions. The paper describes the loss-handling mechanism, retransmission process, and methods for clock synchronization and maintaining continuous packet numbering in the event of a module or base station restart. A series of tests were conducted in various operating modes, with different numbers of modules, at different distances, and under obstacle-induced interference. Experimental results show that the average packet loss rate when using the proposed algorithm does not exceed 1%, and the probability of severe losses (over 10%) is effectively eliminated. The system has also demonstrated stable performance under real-world conditions and supports scaling up to 20 modules. The obtained results confirm the efficiency and feasibility of using the ESP-NOW protocol in distributed biomedical IoT systems focused on motion monitoring, patient rehabilitation, biomechanical studies, and prosthetic adaptation support.
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