{"title":"自主、连续、实时患者监测的物联网系统及其在压力损伤管理中的应用","authors":"Sam Mansfield, Eric Vin, K. Obraczka","doi":"10.1109/icdh52753.2021.00021","DOIUrl":null,"url":null,"abstract":"In this paper, we introduce PIMAP, an IoT-based system for continuous, real-time patient monitoring that operates in a fully autonomous fashion, i.e. without the need for human intervention. To our knowledge, PIMAP is the first open system that integrates the basic patient monitoring workflow including sensed data collection, storage, analysis, and real-time visualization. PIMAP's open design allows it to easily integrate a variety of sensors (custom and off-the-shelf), analytics, and visualization. Other novel features of PIMAP include its deployment flexibility, i.e., its ability to be deployed in different configurations depending on the specific application needs, setting, and resources, as well as PIMAP's self-profiling and self-tuning capabilities. While PIMAP can be applied to various patient monitoring applications and settings, in this paper we focus on the unsolved problem of preventing pressure ulcers, or pressure injuries. We describe how PIMAP's design addresses autonomous, continuous, realtime operation to sense, store, analyze, and visualize patient data from a variety of off-the-shelf as well as custom sensors. We present our current PIMAP prototype as well as different PIMAP configuration scenarios, e.g. cloud-based or edge-based deployment options. We also evaluate PIMAP's performance under different workloads and demonstrate its use collecting wearable pressure sensor data in real-world scenarios from patients with high risk of forming pressure injuries.","PeriodicalId":93401,"journal":{"name":"2021 IEEE International Conference on Digital Health (ICDH)","volume":"47 1","pages":"91-102"},"PeriodicalIF":0.0000,"publicationDate":"2021-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"An IoT System for Autonomous, Continuous, Real-Time Patient Monitoring and Its Application to Pressure Injury Management\",\"authors\":\"Sam Mansfield, Eric Vin, K. Obraczka\",\"doi\":\"10.1109/icdh52753.2021.00021\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper, we introduce PIMAP, an IoT-based system for continuous, real-time patient monitoring that operates in a fully autonomous fashion, i.e. without the need for human intervention. To our knowledge, PIMAP is the first open system that integrates the basic patient monitoring workflow including sensed data collection, storage, analysis, and real-time visualization. PIMAP's open design allows it to easily integrate a variety of sensors (custom and off-the-shelf), analytics, and visualization. Other novel features of PIMAP include its deployment flexibility, i.e., its ability to be deployed in different configurations depending on the specific application needs, setting, and resources, as well as PIMAP's self-profiling and self-tuning capabilities. While PIMAP can be applied to various patient monitoring applications and settings, in this paper we focus on the unsolved problem of preventing pressure ulcers, or pressure injuries. We describe how PIMAP's design addresses autonomous, continuous, realtime operation to sense, store, analyze, and visualize patient data from a variety of off-the-shelf as well as custom sensors. We present our current PIMAP prototype as well as different PIMAP configuration scenarios, e.g. cloud-based or edge-based deployment options. We also evaluate PIMAP's performance under different workloads and demonstrate its use collecting wearable pressure sensor data in real-world scenarios from patients with high risk of forming pressure injuries.\",\"PeriodicalId\":93401,\"journal\":{\"name\":\"2021 IEEE International Conference on Digital Health (ICDH)\",\"volume\":\"47 1\",\"pages\":\"91-102\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-09-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2021 IEEE International Conference on Digital Health (ICDH)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/icdh52753.2021.00021\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 IEEE International Conference on Digital Health (ICDH)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/icdh52753.2021.00021","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
An IoT System for Autonomous, Continuous, Real-Time Patient Monitoring and Its Application to Pressure Injury Management
In this paper, we introduce PIMAP, an IoT-based system for continuous, real-time patient monitoring that operates in a fully autonomous fashion, i.e. without the need for human intervention. To our knowledge, PIMAP is the first open system that integrates the basic patient monitoring workflow including sensed data collection, storage, analysis, and real-time visualization. PIMAP's open design allows it to easily integrate a variety of sensors (custom and off-the-shelf), analytics, and visualization. Other novel features of PIMAP include its deployment flexibility, i.e., its ability to be deployed in different configurations depending on the specific application needs, setting, and resources, as well as PIMAP's self-profiling and self-tuning capabilities. While PIMAP can be applied to various patient monitoring applications and settings, in this paper we focus on the unsolved problem of preventing pressure ulcers, or pressure injuries. We describe how PIMAP's design addresses autonomous, continuous, realtime operation to sense, store, analyze, and visualize patient data from a variety of off-the-shelf as well as custom sensors. We present our current PIMAP prototype as well as different PIMAP configuration scenarios, e.g. cloud-based or edge-based deployment options. We also evaluate PIMAP's performance under different workloads and demonstrate its use collecting wearable pressure sensor data in real-world scenarios from patients with high risk of forming pressure injuries.