{"title":"A virtual/digital pet Point-of-Care system for self-management of COPD patients","authors":"D. Arvind, T. Georgescu, W. Bao, C. A. Bates","doi":"10.1109/HI-POCT54491.2022.9744060","DOIUrl":null,"url":null,"abstract":"Pulmonary rehabilitation is recommended for COPD patients to help manage their long-term condition. The objectives of the point-of-care system are: remote observability of patients by continuous monitoring of their vital signs of respiratory rate and respiratory effort; encourage adherence to the pulmonary rehabilitation regime and correct execution of the exercises. The point-of-care system consists of the Respeck sensor device worn as a plaster on the chest to monitor respiratory rate/flow and physical activity, and a mobile app to (i) orchestrate the pulmonary rehabilitation exercises; (ii) an e-pet to engage the patient to exercise regularly; (iii) handle communication of Respeck data with the Cloud-based server. A dashboard provides the Care Team of physiotherapists, respiratory nurses and doctors with (i) the current status and historical trends of breathing rate/flow; (ii) classification of their static (lying down, sitting/standing, and dynamic (walking, running, climbing stairs) physical activities; (iii) correctness and frequency of their pulmonary rehabilitation exercises; (iv) level of interaction with their virtual/digital pet. Results are presented on the evaluation of the virtual/digital feature by respiratory physiotherapists ahead of deployment with COPD patients.Clinical Relevance—The point-of-care system can classify the correctness of the ten pulmonary rehabilitation exercises using machine learning techniques with a maximum accuracy of 93% to provide the Care Team confidence their charges are performing exercises correctly when unsupervised. Results are summarised for a survey of nine pulmonary physiotherapists on their evaluation of the efficacy of using the Respeck and the App in a Point-of-Care system (POCS) for COPD patients.","PeriodicalId":283503,"journal":{"name":"2022 IEEE Healthcare Innovations and Point of Care Technologies (HI-POCT)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-03-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 IEEE Healthcare Innovations and Point of Care Technologies (HI-POCT)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/HI-POCT54491.2022.9744060","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Pulmonary rehabilitation is recommended for COPD patients to help manage their long-term condition. The objectives of the point-of-care system are: remote observability of patients by continuous monitoring of their vital signs of respiratory rate and respiratory effort; encourage adherence to the pulmonary rehabilitation regime and correct execution of the exercises. The point-of-care system consists of the Respeck sensor device worn as a plaster on the chest to monitor respiratory rate/flow and physical activity, and a mobile app to (i) orchestrate the pulmonary rehabilitation exercises; (ii) an e-pet to engage the patient to exercise regularly; (iii) handle communication of Respeck data with the Cloud-based server. A dashboard provides the Care Team of physiotherapists, respiratory nurses and doctors with (i) the current status and historical trends of breathing rate/flow; (ii) classification of their static (lying down, sitting/standing, and dynamic (walking, running, climbing stairs) physical activities; (iii) correctness and frequency of their pulmonary rehabilitation exercises; (iv) level of interaction with their virtual/digital pet. Results are presented on the evaluation of the virtual/digital feature by respiratory physiotherapists ahead of deployment with COPD patients.Clinical Relevance—The point-of-care system can classify the correctness of the ten pulmonary rehabilitation exercises using machine learning techniques with a maximum accuracy of 93% to provide the Care Team confidence their charges are performing exercises correctly when unsupervised. Results are summarised for a survey of nine pulmonary physiotherapists on their evaluation of the efficacy of using the Respeck and the App in a Point-of-Care system (POCS) for COPD patients.