与个人排便相关的肠音信号数据集

本数据集主要面向肠道生理信号分析与排便健康预警研究，服务于临床护理、老年健康监测及智能便意识别需求建设。数据基于高精度肠音传感器，在2023年1月至2025年12月期间，于受试者左下腹部结直肠交界处附近持续采集产生，主要记录了空腹、饭后、排便前、排便后四种生理状态下的肠鸣音时序信号，采样率为2000 Hz。数据集共包含受试者的多状态音频数据，每次采集持续10-20分钟，以CSV格式存储原始采样点序列，体量约为200MB。数据通过实时肠鸣音解码与个体排便节律模型进行处理，旨在实现高准确率的便意识别与预警，为肠道功能评估、行为预测及辅助护理系统开发提供可靠的生理信号依据。This dataset is primarily developed for research on intestinal physiological signal analysis and bowel movement health early warning, catering to the demands of clinical nursing, elderly health monitoring, and intelligent defecation awareness recognition systems. The data was continuously collected via high-precision bowel sound sensors near the colorectal-junctional region of the left lower abdomen from January 2023 to December 2025, primarily capturing bowel sound time-series signals under four physiological conditions: fasting, post-prandial, pre-defecation, and post-defecation, with a sampling rate of 2000 Hz. The dataset comprises multi-state audio data from multiple subjects, with each acquisition session lasting 10 to 20 minutes. Raw sampling point sequences are stored in CSV format, and the total dataset size is approximately 200 MB. The data is processed using real-time bowel sound decoding and individual defecation rhythm models, aiming to achieve high-accuracy defecation awareness recognition and early warning, providing reliable physiological signal foundations for intestinal function assessment, behavior prediction, and the development of assisted nursing systems.

搜集汇总

背景与挑战

背景概述

该数据集面向肠道生理信号分析与排便健康预警研究，服务于临床护理和老年健康监测等需求。它通过高精度传感器采集了受试者在空腹、饭后、排便前和排便后四种状态下的肠鸣音时序信号，采样率为2000 Hz，数据以CSV格式存储，体量约为200MB。数据集旨在支持便意识别与预警，为肠道功能评估和辅助护理系统开发提供生理信号依据。