{"title":"利用自适应兴趣区和混合处理方法开发带有远程血压计的非接触式人体生命体征监测设备","authors":"Dessy Novita , Fajar Wira Adikusuma , Nanang Rohadi , Bambang Mukti Wibawa , Agus Trisanto , Irma Ruslina Defi , Sherllina Rizqi Fauziah","doi":"10.1016/j.ibmed.2024.100160","DOIUrl":null,"url":null,"abstract":"<div><p>Vital sign assessment is an examination that indicates changes in health. Direct contact during vital signs assessment can increase the risk of disease transmission. This research aimed to develop a contactless vital sign monitoring prototype that includes heart rate, respiratory rate, blood pressure, and oxygen saturation using a digital camera based on remote photoplethysmography with an adaptive region of interest. The adaptive region-of-interest method uses face detection and skin segmentation to generate red-green-blue signals, taking only the skin pixels of the patients while also minimising the effect of motion artefacts. The hybrid processing method combines several vital sign extraction methods to filter external irrelevant factors and produce heart rate, respiratory rate, blood pressure, and blood oxygen saturation values. In addition, the prototype was tested on 50 participants using standard vital sign assessment tools for comparison. The technical specification test of the prototype concluded that the optimal distance of this prototype was up to 2 m with a processing time of 2 s for every 1-s video. The vital signs results were presented using Bland-Altman, which showed that although the Bland-Altman plots revealed a substantial variance in the limits of agreement (±15–20 mmHg for blood pressure, ±15–17 bpm for heart rate, ±4–6 bpm for respiratory rate, and ±1–3 % for blood oxygen saturation), the mean differences for all vital signs were small (±0.7–5 mmHg for blood pressure, ±0.4–0.6 bpm for heart rate, ±0.5–0.7 bpm for respiratory rate, ±0.4–0.6 for blood oxygen saturation) and most data points were within the limits. While further clinical studies are needed to assess its reliability in monitoring specific medical conditions, the prototype has shown an acceptable agreement in assessing vital signs compared to the conventional methods, making it feasible for further development into a medical device.</p></div>","PeriodicalId":73399,"journal":{"name":"Intelligence-based medicine","volume":"10 ","pages":"Article 100160"},"PeriodicalIF":0.0000,"publicationDate":"2024-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2666521224000279/pdfft?md5=9c2a08467d4ad925fd1a09dfb6f59ae1&pid=1-s2.0-S2666521224000279-main.pdf","citationCount":"0","resultStr":"{\"title\":\"Development of contactless human vital signs monitoring device with remote-photoplethysmography using adaptive region-of-interest and hybrid processing methods\",\"authors\":\"Dessy Novita , Fajar Wira Adikusuma , Nanang Rohadi , Bambang Mukti Wibawa , Agus Trisanto , Irma Ruslina Defi , Sherllina Rizqi Fauziah\",\"doi\":\"10.1016/j.ibmed.2024.100160\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>Vital sign assessment is an examination that indicates changes in health. Direct contact during vital signs assessment can increase the risk of disease transmission. This research aimed to develop a contactless vital sign monitoring prototype that includes heart rate, respiratory rate, blood pressure, and oxygen saturation using a digital camera based on remote photoplethysmography with an adaptive region of interest. The adaptive region-of-interest method uses face detection and skin segmentation to generate red-green-blue signals, taking only the skin pixels of the patients while also minimising the effect of motion artefacts. The hybrid processing method combines several vital sign extraction methods to filter external irrelevant factors and produce heart rate, respiratory rate, blood pressure, and blood oxygen saturation values. In addition, the prototype was tested on 50 participants using standard vital sign assessment tools for comparison. The technical specification test of the prototype concluded that the optimal distance of this prototype was up to 2 m with a processing time of 2 s for every 1-s video. The vital signs results were presented using Bland-Altman, which showed that although the Bland-Altman plots revealed a substantial variance in the limits of agreement (±15–20 mmHg for blood pressure, ±15–17 bpm for heart rate, ±4–6 bpm for respiratory rate, and ±1–3 % for blood oxygen saturation), the mean differences for all vital signs were small (±0.7–5 mmHg for blood pressure, ±0.4–0.6 bpm for heart rate, ±0.5–0.7 bpm for respiratory rate, ±0.4–0.6 for blood oxygen saturation) and most data points were within the limits. While further clinical studies are needed to assess its reliability in monitoring specific medical conditions, the prototype has shown an acceptable agreement in assessing vital signs compared to the conventional methods, making it feasible for further development into a medical device.</p></div>\",\"PeriodicalId\":73399,\"journal\":{\"name\":\"Intelligence-based medicine\",\"volume\":\"10 \",\"pages\":\"Article 100160\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.sciencedirect.com/science/article/pii/S2666521224000279/pdfft?md5=9c2a08467d4ad925fd1a09dfb6f59ae1&pid=1-s2.0-S2666521224000279-main.pdf\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Intelligence-based medicine\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S2666521224000279\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Intelligence-based medicine","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2666521224000279","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Development of contactless human vital signs monitoring device with remote-photoplethysmography using adaptive region-of-interest and hybrid processing methods
Vital sign assessment is an examination that indicates changes in health. Direct contact during vital signs assessment can increase the risk of disease transmission. This research aimed to develop a contactless vital sign monitoring prototype that includes heart rate, respiratory rate, blood pressure, and oxygen saturation using a digital camera based on remote photoplethysmography with an adaptive region of interest. The adaptive region-of-interest method uses face detection and skin segmentation to generate red-green-blue signals, taking only the skin pixels of the patients while also minimising the effect of motion artefacts. The hybrid processing method combines several vital sign extraction methods to filter external irrelevant factors and produce heart rate, respiratory rate, blood pressure, and blood oxygen saturation values. In addition, the prototype was tested on 50 participants using standard vital sign assessment tools for comparison. The technical specification test of the prototype concluded that the optimal distance of this prototype was up to 2 m with a processing time of 2 s for every 1-s video. The vital signs results were presented using Bland-Altman, which showed that although the Bland-Altman plots revealed a substantial variance in the limits of agreement (±15–20 mmHg for blood pressure, ±15–17 bpm for heart rate, ±4–6 bpm for respiratory rate, and ±1–3 % for blood oxygen saturation), the mean differences for all vital signs were small (±0.7–5 mmHg for blood pressure, ±0.4–0.6 bpm for heart rate, ±0.5–0.7 bpm for respiratory rate, ±0.4–0.6 for blood oxygen saturation) and most data points were within the limits. While further clinical studies are needed to assess its reliability in monitoring specific medical conditions, the prototype has shown an acceptable agreement in assessing vital signs compared to the conventional methods, making it feasible for further development into a medical device.