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The system compares each patient’s respiratory-rate circadian rhythm over the prior two weeks with that of the most recent 24 hours, using non-contact vital measurement under a mattress. It aims to identify acute exacerbation before physician diagnosis when conventional threshold vital signs show no change.",{"@graph":69,"@context":123},[70,84,106],{"@type":71,"itemListElement":72},"BreadcrumbList",[73,77,79,82],{"item":74,"name":75,"@type":76,"position":8},"https://docshare.wps.com","Home","ListItem",{"item":78,"name":9,"@type":76,"position":14},"https://docshare.wps.com/document/",{"item":80,"name":35,"@type":76,"position":81},"https://docshare.wps.com/document/healthcare/",3,{"item":83,"name":65,"@type":76,"position":19},"https://docshare.wps.com/document/preliminary-detection-of-acute-exacerbation-of-lobar-pneumonia-and-heart-failure-using-an-anomaly-detection-system-based-on-a-circadian-rhythm-model-constructed-from-non-contact-vital-data/434568/",{"url":83,"name":65,"@type":85,"image":86,"author":91,"headline":65,"publisher":94,"fileFormat":97,"inLanguage":63,"description":67,"dateModified":98,"datePublished":99,"encodingFormat":97,"isAccessibleForFree":100,"interactionStatistic":101},"DigitalDocument",{"url":87,"@type":88,"width":89,"height":90},"https://docshare.wps.com/thumbnails/preliminary-detection-of-acute-exacerbation-of-lobar-pneumonia-and-heart-failure-using-an-anomaly-detection-system-based-on-a-circadian-rhythm-model-constructed-from-non-contact-vital-data/434568.png","ImageObject",300,407,{"name":92,"@type":93},"Fahsai","Person",{"url":74,"name":95,"@type":96},"DocShare","Organization","application/pdf","2026-11-08","2026-09-29",true,{"@type":102,"interactionType":103,"userInteractionCount":105},"InteractionCounter",{"@type":104},"ViewAction",11,{"@type":107,"mainEntity":108},"FAQPage",[109,115,119],{"name":110,"@type":111,"acceptedAnswer":112},"Why is a conventional vital-sign threshold difficult for detecting exacerbation in older patients?","Question",{"text":113,"@type":114},"Frail older patients with multiple comorbidities and immunosuppressive states show large inter-individual differences in weakness, slowness, and asymptomatic status. These differences make fixed thresholds unreliable.","Answer",{"name":116,"@type":111,"acceptedAnswer":117},"How does the anomaly-detection system work?",{"text":118,"@type":114},"It builds a circadian rhythm model for each patient from measured respiratory rate, comparing the past two weeks’ average rhythm with the last 24 hours. Abnormality is evaluated using residuals and periodicity-based criteria.",{"name":120,"@type":111,"acceptedAnswer":121},"How is respiratory rate measured in the system?",{"text":122,"@type":114},"Respiratory rate is obtained from a piezoelectric sensor placed under the patient’s mattress that detects subtle bed movements at about 1 Hz. Body-movement artifacts are excluded from calculations.","https://schema.org",{"og:url":83,"og:type":125,"og:title":65,"og:site_name":95,"og:description":67},"article",{"robots":127,"canonical":83},"index,follow",{"doc_id":129,"site_id":62},434568,1790916355,{"code":4,"msg":5,"data":132},{"doc_id":129,"user_id":133,"nickname":92,"user_avatar":134,"doc_module":4,"category_id":34,"category_name":35,"doc_title":65,"doc_description":67,"doc_content":135,"file_id":136,"file_url":137,"file_type":138,"file_size":139,"view_count":105,"is_deleted":4,"is_public":8,"is_downloadable":8,"audit_status":8,"page_count":24,"language":140,"language_code":63,"site_id":62,"html_lang":63,"table_of_contents":141,"faqs":142,"seo_title":143,"seo_description":67,"update_tm":144,"read_time":145,"preview_page_count":4},549768702563,"https://ap-avatar.wpscdn.com/avatar/8000c4aa63b76e948b?x-image-process=image/resize,m_fixed,w_180,h_180&k=1786536092046926083","Preliminary Detection of Acute Exacerbation of Lobar Pneumonia and Heart Failure Using an Anomaly-Detection System Basedona Circadian Rhythm Model Constructed from Non-contact Vital Data  \nTsuyoshi Kobayashi1,2*, Kenichi Hashimoto3,4*, Takemi Matsui1  \n1Graduate School of Systems Design, Tokyo Metropolitan University, Tokyo, Japan 2Konica Minolta Inc., Tokyo, Japan  \n3Medical Education and Clinical Training Center, Division of Clinical Training Management, National Defense Medical College, Tokorozawa, Saitama, Japan 4Department of General Medicine, National Defense Medical College, Tokorozawa, Saitama, Japan  \nCorresponding Author:  \nTsuyoshi Kobayashi, D.Eng.  \nKonica Minolta Inc., 1, Sakura-machi, Hino-shi, Tokyo 192-8505, Japan E-mail: tsuyoshi.kobayashi@ [konicaminolta.com](konicaminolta.com)  \nORCID:  \n[https://orcid.org/0009-0005-4120-4098](https://orcid.org/0009-0005-4120-4098)  \n*These authors contributed equally to this work.  \nReceived: April 10, 2025  \nRevised: June 16, 2025  \nAccepted: June 23, 2025  \nMany frail older patients with multiple comorbidities are hospitalized in long-term care hospitalsand nursing facilities. Due to pre-existing conditions and immunosuppressive states, there are significant individual differences, such as weakness, sluggishness, and asymptomatic status. These differences make it challenging to find a patient’s exacerbation using a conventional threshold of vital signs. We developed a circadian rhythm anomaly-detection system designed for each patient, which compares each patient’s past 2 weeks average respiratory rate circadian rhythm with that of the last 24 hours. Respiratory rate was measured using a piezoelectric sensor located under the mattress. Prior to the doctor’s diagnosis of acute exacerbation of lobar pneumonia and heart failure, a bedridden 88-year-old female patient with multiple chronic diseases showed abnormal circadian rhythm status. However, there were no significant changes in vital signs. A circadian rhythm anomaly-detection system appears promising as a future tool to promote medical checkups for the older person.  \nKey Words: Circadian rhythm, Older person, Pneumonia, Acute exacerbation, Respiratory rate  \nINTRODUCTION  \nThe number of older people is increasing worldwide. In Japan, many frail older people with multiple comorbidities are hospitalized in chronic care wards and nursing homes, some of whom experience sudden changes in their conditions. In addition, a nationwide shortage of nurses, caregivers, and other staff members makes it difficult to monitor all patients’ conditions, highlighting the need to develop a suitable monitoring system.1) A patient’s condition is monitored by measuring their vital signs; however, these demonstrate significant inter-individual differences, such as weakness, slowness, and asymptomatic state, due to the patient’s pre-existing diseases2) and immunosuppression.3) These differences cannot be accounted for by employing a uniform vital threshold.  \nHeart failure causes central sleep apnea with Cheyne-Stokes respiration, disrupting the circadian rhythm of the respiratory rate (RR),4) while lung inflammation itself also disrupts the circadian rhythm oftheRR.5)  \nWe developed a circadian rhythm anomaly-detection system tailored for each patient. This system compares each patient’s average respiratory rate circadian rhythm over the past 2 weeks with that of the last 24 hours.  \nHere, we report the use of a circadian rhythm anomaly-detection system based on a circadian rhythm model created from the measured RR that was applied in older people and which predicted the early onset of heart failure and lobar pneumonia in a patient with no changes in conventional vital threshold .  \n© 2025 by The Korean Geriatrics Society  \nThis is an open access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (https://creativecommons.org/licenses/by-nc/4.0/) which permits unrestricted non-commercial use, distr","cbCaivR9RRfA5yoV","https://ap.wps.com/l/cbCaivR9RRfA5yoV","pdf",768006,"English","# Key Words\n# INTRODUCTION\n# CASE DESCRIPTION","[{\"question\":\"Why is a conventional vital-sign threshold difficult for detecting exacerbation in older patients?\",\"answer\":\"Frail older patients with multiple comorbidities and immunosuppressive states show large inter-individual differences in weakness, slowness, and asymptomatic status. These differences make fixed thresholds unreliable.\"},{\"question\":\"How does the anomaly-detection system work?\",\"answer\":\"It builds a circadian rhythm model for each patient from measured respiratory rate, comparing the past two weeks’ average rhythm with the last 24 hours. Abnormality is evaluated using residuals and periodicity-based criteria.\"},{\"question\":\"How is respiratory rate measured in the system?\",\"answer\":\"Respiratory rate is obtained from a piezoelectric sensor placed under the patient’s mattress that detects subtle bed movements at about 1 Hz. Body-movement artifacts are excluded from calculations.\"}]","Preliminary Detection of Acute Exacerbation of Lobar Pneumonia and Heart Failure Using an Anomaly-Detection System Based on a Circadian Rhythm Model Constructed from Non-contact Vital Data | PDF",1790669863,13]