Comprehensive Patient-Health Monitoring Dataset

The Comprehensive Patient-Health Monitoring Dataset is an extensive collection of health-related data gathered from remote monitoring systems between June 4, 2023, and October 4, 2023. This dataset comprises 10,000 samples, each meticulously recorded at ten-minute intervals, capturing a diverse array of vital signs and health metrics crucial for patient care and medical research. Key attributes included in the dataset are timestamps, heart rate (bpm), blood pressure (systolic/diastolic mmHg), respiratory rate (breaths per minute), body temperature (°C), blood oxygen level (SpO2 %), and glucose level (mg/dL). These parameters are fundamental indicators of an individual’s health status, providing a comprehensive view of their physiological state over time.The dataset is structured to facilitate ease of use for various analytical and research purposes. Each record is timestamped, ensuring accurate chronological tracking of patient health metrics. Heart rate measurements are presented in beats per minute (bpm), blood pressure readings include both systolic and diastolic values (mmHg), respiratory rate is captured in breaths per minute, body temperature is recorded in degrees Celsius, blood oxygen levels are expressed as a percentage of SpO2, and glucose levels are noted in mg/dL. The data format ensures compatibility with a wide range of analytical tools and statistical software, making it accessible for researchers across different disciplines.This dataset holds significant potential for a wide array of research applications in the healthcare field. Its extensive temporal coverage and detailed vital sign measurements make it a valuable resource for studying trends and patterns in patient health over time. Researchers can leverage this dataset to develop and validate predictive models for early disease detection, patient deterioration prediction, and personalized health interventions. Moreover, the dataset can support the evaluation and improvement of remote monitoring technologies and telemedicine practices, contributing to the enhancement of patient care in non-clinical settings. 

综合患者健康监护数据集是2023年6月4日至2023年10月4日期间从远程监护系统（remote monitoring system）采集的大规模健康相关数据集合。本数据集共包含10000条样本，所有样本均以十分钟为间隔精心记录，涵盖了患者护理与医学研究所需的各类关键生命体征（vital signs）与健康指标（health metrics）。数据集涵盖的核心属性包括：时间戳、心率（heart rate，bpm）、血压（blood pressure，收缩压/舒张压，mmHg）、呼吸频率（respiratory rate，breaths per minute）、体温（body temperature，°C）、血氧水平（blood oxygen level，SpO2 %）以及血糖水平（glucose level，mg/dL）。上述参数均为反映个体健康状态的核心指标，可全面呈现其随时间变化的生理状况。
本数据集的结构设计旨在便于各类分析与研究工作的开展，每条记录均附带时间戳，可精准追踪患者健康指标的时间序列变化。其中，心率测量值以次/分钟（bpm）为单位呈现，血压读数包含收缩压与舒张压两项指标（单位：mmHg），呼吸频率以呼吸次数/分钟为单位记录，体温采用摄氏度（°C）为单位，血氧水平以SpO2百分比表示，血糖水平则以mg/dL为单位标注。该数据集的格式兼容多款分析工具与统计软件，可为不同学科领域的研究人员提供便捷使用的可能。
本数据集在医疗领域具备广泛的研究应用潜力，其丰富的时间跨度与详尽的生命体征测量数据，为研究患者健康随时间变化的趋势与模式提供了宝贵的资源。研究人员可借助本数据集开发并验证预测模型（predictive models），用于疾病早期检测、患者病情恶化预测以及个性化健康干预。此外，本数据集还可用于评估与优化远程监护技术及远程医疗（telemedicine）实践，助力提升非临床场景下的患者护理质量。

搜集汇总

背景与挑战

背景概述

该数据集是一个包含10,000个样本的远程健康监测数据集，记录了2023年6月至10月间每10分钟一次的心率、血压、呼吸频率等关键健康指标，适用于疾病预测模型开发和远程医疗技术研究。