2nd International Conference on Internet of Things and Smart City (IoTSC 2022) 2022
DOI: 10.1117/12.2637169
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Non-contact road anger detection device based on millimeter wave radar

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Cited by 1 publication
(2 citation statements)
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“…Nasal breath sound recordings from a smartphone, ECG (PSL-iECG2) X2 (50×70 mm) [83] The upper left of the windshield 7.29 and 8.748 Pulse oximetry X4M300 (50×70 mm) [84] The lower left of the steering wheel 2.4 Self-assessment of the participant for being drowsy Not specified [94] Behind the seat 60 A pressure sensor is worn on the abdomen 50×50 mm [80] Under the steering wheel 77 ECG, Respiration belt IWR1843BOOST [79] Behind the seat 24 ECG Not specified [88] In the driver's seat Millimeter wave Camera, Wearable physiological detection instrument Not specified [67] Rearview mirror 77 Polar H10 heart monitor AWR1642BOOST [68] Rearview mirror 120 Spirometer Not specified [49] The left top side of the subjects' chest 60 A clinical reference sensor BSM6501K IWR6843 [62] Mobile holder (right side of steering wheel) 60 Air-flow, Temperature sensor XM132 (25×20 mm) [65], [69] In front of the chest of the main subject 60 ECG XM112 [71] On the steering wheel 4.3 Edan iM50 Not specified to assess their proposed algorithms for vital sign monitoring inside a car. As can be seen in Table IX, the most common ground truth for the evaluation of estimated HR is pulse oximetry.…”
Section: Referencementioning
confidence: 99%
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“…Nasal breath sound recordings from a smartphone, ECG (PSL-iECG2) X2 (50×70 mm) [83] The upper left of the windshield 7.29 and 8.748 Pulse oximetry X4M300 (50×70 mm) [84] The lower left of the steering wheel 2.4 Self-assessment of the participant for being drowsy Not specified [94] Behind the seat 60 A pressure sensor is worn on the abdomen 50×50 mm [80] Under the steering wheel 77 ECG, Respiration belt IWR1843BOOST [79] Behind the seat 24 ECG Not specified [88] In the driver's seat Millimeter wave Camera, Wearable physiological detection instrument Not specified [67] Rearview mirror 77 Polar H10 heart monitor AWR1642BOOST [68] Rearview mirror 120 Spirometer Not specified [49] The left top side of the subjects' chest 60 A clinical reference sensor BSM6501K IWR6843 [62] Mobile holder (right side of steering wheel) 60 Air-flow, Temperature sensor XM132 (25×20 mm) [65], [69] In front of the chest of the main subject 60 ECG XM112 [71] On the steering wheel 4.3 Edan iM50 Not specified to assess their proposed algorithms for vital sign monitoring inside a car. As can be seen in Table IX, the most common ground truth for the evaluation of estimated HR is pulse oximetry.…”
Section: Referencementioning
confidence: 99%
“…Mechanical sensors can be divided into three common categories, including resistive [8], inductive [9], and capacitive [10]. Both resistive 2 Range-doppler map or timefrequency spectrum Artificial intelligence to detect occupied seats [3], [11]- [34] The amplitude of reflected signals Left-behind child [2], [35]- [48] BR and HR difference BR and HR estimation [49]- [51] Gesture recognition to assist drivers Micro-doppler features Artificial intelligence to detect gestures [52]- [59] Occupant status monitoring BR and/or HR estimation None [60]- [77] Sensor placement for accurate BR estimation [78]- [80] Vital sign monitoring in an ambulance [81] Drowsy driving detection [82]- [87] Biometric driver seat [79] Angry driver [88] Multiple targets vital sign monitoring [89], [90] Car vibrations suppression [62], [91]- [93] Changes in the reflected power Distracted driver detection by cellphone [82] Random body movement cancellation [62], [80], [94] Airbag [95] Range-doppler map Distracted/drowsy driver based on head motion [96]- [101] Range doppler map, Changes in the phase of signals Drowsy driver based on eye blink frequency [102]- [107] and inductive sensors have difficulty discriminating between humans and objects [3]. Capacitive sensors which can detect the dielectric dispersion effects on human tissues are prone to high false detections…”
Section: Introductionmentioning
confidence: 99%