title: An infectious disease/fever screening radar system which stratifies higher-risk patients within ten seconds using a neural network and the fuzzy grouping method.
abstract: OBJECTIVE
  To classify higher-risk influenza patients within 10 s, we developed an infectious disease and fever screening radar system.
  
  
  METHODS
  The system screens infected patients based on vital signs, i.e., respiration rate measured by a radar, heart rate by a finger-tip photo-reflector, and facial temperature by a thermography. The system segregates subjects into higher-risk influenza (HR-I) group, lower-risk influenza (LR-I) group, and non-influenza (Non-I) group using a neural network and fuzzy clustering method (FCM). We conducted influenza screening for 35 seasonal influenza patients and 48 normal control subjects at the Japan Self-Defense Force Central Hospital. Pulse oximetry oxygen saturation (SpO2) was measured as a reference.
  
  
  RESULTS
  The system classified 17 subjects into HR-I group, 26 into LR-I group, and 40 into Non-I group. Ten out of the 17 HR-I subjects indicated SpO2 <96%, whereas only two out of the 26 LR-I subjects showed SpO2 <96%. The chi-squared test revealed a significant difference in the ratio of subjects showed SpO2 <96% between HR-I and LR-I group (p < 0.001). There were zero and nine normal control subjects in HR-I and LR-I groups, respectively, and there was one influenza patient in Non-I group.
  
  
  CONCLUSIONS
  The combination of neural network and FCM achieved efficient detection of higher-risk influenza patients who indicated SpO2 96% within 10 s.
authors.affiliation: Graduate School of System Design, Tokyo Metropolitan University, 6-6 Asahigaoka, Hino, Tokyo 191-0065, Japan. Electronic address: sun-guanghao@ed.tmu.ac.jp.
authors.forename: Guanghao
authors.initials: G
authors.lastname: Sun
authors.affiliation: Graduate School of System Design, Tokyo Metropolitan University, 6-6 Asahigaoka, Hino, Tokyo 191-0065, Japan. Electronic address: tmatsui@tmu.ac.jp.
authors.forename: Takemi
authors.initials: T
authors.lastname: Matsui
authors.affiliation: Department of Internal Medicine, Japan Self-Defense Forces Central Hospital, 1-2-24 Ikejiri, Setagaya, Tokyo 154-0001, Japan.
authors.forename: Yukiya
authors.initials: Y
authors.lastname: Hakozaki
authors.affiliation: Takasaka Clinic, 172-21 Kanesaka, Uchigomiya, Iwaki, Fukushima 973-8407, Japan.
authors.forename: Shigeto
authors.initials: S
authors.lastname: Abe
mesh_terms: D000368:Aged; D015374:Biosensing Techniques; D005260:Female; D005334:Fever / Q000175:diagnosis*; D006339:Heart Rate; D006801:Humans; D007251:Influenza, Human / Q000145:classification / Q000175:diagnosis*; D007564:Japan; D008297:Male; D008403:Mass Screening / Q000379:methods*; D008875:Middle Aged; D016571:Neural Networks, Computer; D010092:Oximetry; D011825:Radar; D056152:Respiratory Rate; D012680:Sensitivity and Specificity; D013817:Thermography / Q000379:methods
keywords: Influenza; Mass screening; Microwave radar; Oxygen saturation; Thermography; Vital signs