"High-Resolution ECG Telemetry Dataset: Adaptive Soldier Telemetry & Reconnaissance Array (A.S.T.R.A.)"

"This dataset contains physiological telemetry data recorded during the active development of Project A.S.T.R.A. (Adaptive Soldier Telemetry & Reconnaissance Array), a ruggedized wearable telemetry system designed for high-stress and defense applications.The hardware architecture utilizes an AD8232 single-lead ECG analog front-end interfaced with a Seeed Studio XIAO ESP32S3 Sense microcontroller. The ESP32 handles the analog-to-digital conversion and onboard Digital Signal Processing (DSP). Telemetry was captured from a 20-year-old male undergraduate Electronics and Communication Engineering student (acting as the primary hardware innovator) during the prototyping phase.The data\u2014comprising raw ADC values, filtered ADC values, and a dedicated hardware fault flag\u2014was transmitted in real-time via a high-speed UART serial connection and captured via a MATLAB data acquisition script. This dataset provides a side-by-side comparison of raw versus real-time filtered signals, making it highly optimized for researchers validating custom DSP algorithms, baseline wandering removal techniques and edge-AI predictive maintenance models for autonomous sensor-fault detection."

本数据集收录了A.S.T.R.A.项目（Adaptive Soldier Telemetry & Reconnaissance Array，自适应士兵遥测与侦察阵列）研发活跃期记录的生理遥测数据。该项目是一款面向高应激场景与国防应用的加固型可穿戴遥测系统。其硬件架构采用AD8232单导联心电图（Electrocardiogram, ECG）模拟前端，与Seeed Studio XIAO ESP32S3 Sense微控制器相连。ESP32负责完成模数转换与板载数字信号处理（Digital Signal Processing, DSP）。遥测数据采集于原型机开发阶段，受试者为一名20岁男性电子与通信工程专业本科生，同时也是该项目的核心硬件研发人员。本次采集的数据包含原始模数转换（Analog-to-Digital Conversion, ADC）值、滤波后ADC值以及专用硬件故障标记位，通过高速通用异步收发传输器（Universal Asynchronous Receiver/Transmitter, UART）串行连接实时传输，并由MATLAB数据采集脚本完成捕获。本数据集提供原始信号与实时滤波信号的平行对照结果，可为验证自定义DSP算法、基线漂移去除技术，以及用于自主传感器故障检测的边缘人工智能（Edge AI）预测性维护模型的研究工作提供高度优化的支持。