A. Copiaco, C. Ritz, Stefano Fasciani, N. Abdulaziz
{"title":"用声级评估工具监测痴呆患者的应用","authors":"A. Copiaco, C. Ritz, Stefano Fasciani, N. Abdulaziz","doi":"10.1109/ICSPIS51252.2020.9340131","DOIUrl":null,"url":null,"abstract":"Dementia is an ailment heavily associated with cognitive decline and old age. Due to its progressive nature, several changes in sensory perceptions may be experienced by the individual. Thus, consistent monitoring of patients' assistance requirement, as well as the noise levels throughout their environment, can pose a challenge to caretakers. This is especially apparent for healthcare professionals working in nursing facilities. In this work, we propose an application with an intuitive interface that allows the acoustic monitoring of the patient without infringing their privacy. This is achieved through neural network-based sound scene classification and source location estimation models, which are trained with results of 98.80% and 99.68% F1-scores, respectively. Further, a sound level assessment tool is implemented, such that the time-average levels of the sound are compared to the recommended levels depending on the specific location and time of the day. Experimentation and implementation is carried out in MATLAB, while the interface was developed through the MATLAB App Designer, which can be exported into a mobile phone application as per required.","PeriodicalId":373750,"journal":{"name":"2020 3rd International Conference on Signal Processing and Information Security (ICSPIS)","volume":"82 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-11-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"An Application for Dementia Patient Monitoring with Sound Level Assessment Tool\",\"authors\":\"A. Copiaco, C. Ritz, Stefano Fasciani, N. Abdulaziz\",\"doi\":\"10.1109/ICSPIS51252.2020.9340131\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Dementia is an ailment heavily associated with cognitive decline and old age. Due to its progressive nature, several changes in sensory perceptions may be experienced by the individual. Thus, consistent monitoring of patients' assistance requirement, as well as the noise levels throughout their environment, can pose a challenge to caretakers. This is especially apparent for healthcare professionals working in nursing facilities. In this work, we propose an application with an intuitive interface that allows the acoustic monitoring of the patient without infringing their privacy. This is achieved through neural network-based sound scene classification and source location estimation models, which are trained with results of 98.80% and 99.68% F1-scores, respectively. Further, a sound level assessment tool is implemented, such that the time-average levels of the sound are compared to the recommended levels depending on the specific location and time of the day. Experimentation and implementation is carried out in MATLAB, while the interface was developed through the MATLAB App Designer, which can be exported into a mobile phone application as per required.\",\"PeriodicalId\":373750,\"journal\":{\"name\":\"2020 3rd International Conference on Signal Processing and Information Security (ICSPIS)\",\"volume\":\"82 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-11-25\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2020 3rd International Conference on Signal Processing and Information Security (ICSPIS)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICSPIS51252.2020.9340131\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 3rd International Conference on Signal Processing and Information Security (ICSPIS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICSPIS51252.2020.9340131","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
An Application for Dementia Patient Monitoring with Sound Level Assessment Tool
Dementia is an ailment heavily associated with cognitive decline and old age. Due to its progressive nature, several changes in sensory perceptions may be experienced by the individual. Thus, consistent monitoring of patients' assistance requirement, as well as the noise levels throughout their environment, can pose a challenge to caretakers. This is especially apparent for healthcare professionals working in nursing facilities. In this work, we propose an application with an intuitive interface that allows the acoustic monitoring of the patient without infringing their privacy. This is achieved through neural network-based sound scene classification and source location estimation models, which are trained with results of 98.80% and 99.68% F1-scores, respectively. Further, a sound level assessment tool is implemented, such that the time-average levels of the sound are compared to the recommended levels depending on the specific location and time of the day. Experimentation and implementation is carried out in MATLAB, while the interface was developed through the MATLAB App Designer, which can be exported into a mobile phone application as per required.