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1.
Annu Int Conf IEEE Eng Med Biol Soc ; 2020: 4349-4352, 2020 07.
Article in English | MEDLINE | ID: mdl-33018958

ABSTRACT

Video Photoplethysmography (vPPG) allows for estimation of blood volume pulse (BVP) from the skin by means of a video camera recording at high frequency rate. The estimation procedure presents several drawbacks in its application to real world conditions, such as light changes or movements that often generate artifacts in the extracted BVP waveform. In addition, the process requires a skin segmentation algorithm to distinguish skin pixels from the background. To date, even the most refined skin segmentation algorithms still need a manual definition that could lead to incorrect pixel classification, and consequently to a decrease in the signal-to-noise ratio (SNR). We here propose a fully autonomic procedure able to extract BVP from video recordings of the skin in real world conditions.The experimental protocol is designed to record the signals of interest and to evaluate changes in the Autonomic Nervous System modulation of the heart during a baseline condition and a controlled breathing phase. Video recordings are gathered from 4 young healthy subjects (age: 21±1 years). vPPG signals are processed in order to extract the BVP waveform, and a peak detection algorithm detects pulse wave peaks that are then used to compute specific measures of heart rate variability (HRV).The procedure is successfully validated by comparing the extracted HRV measures against those extracted using a finger photoplethysmograph (fPPG) using three different skin segmentation algorithms from BVP signals.


Subject(s)
Autonomic Nervous System , Photoplethysmography , Algorithms , Blood Volume , Heart Rate , Humans , Young Adult
2.
Physiol Meas ; 40(5): 054005, 2019 06 04.
Article in English | MEDLINE | ID: mdl-30970334

ABSTRACT

OBJECTIVE: Indoor microclimate may affect students' wellbeing, cardiac autonomic control and cognitive performance with potential impact on learning capabilities. To assess the effects of classroom temperature variations on the autonomic profile and students' cognitive capabilities. APPROACH: Twenty students attending Humanitas University School, (14M, age 21 ± 3 years) underwent a single-lead ECG continuous recording by a portable device during a 2 h lecture when classroom temperature was set 'neutral' (20 °C-22 °C, Day 1) and when classroom temperature was set to 24 °C-26 °C (Day 2). ECGs were sent by telemetry to a server for off-line analysis. Spectral analysis of RR variability provided indices of cardiac sympathetic (LFnu), vagal (HF, HFnu) and cardiac sympatho-vagal modulation (LF/HF). Symbolic analysis of RR variability provided the percentage of sequences of three heart periods with no significant change in RR interval (0V%) and with two significant variations (2V%) reflecting cardiac sympathetic and vagal modulation, respectively. Students' cognitive performance (memory, verbal comprehension and reasoning) was assessed at the end of each lecture using the Cambridge Brain Sciences cognitive evaluation tool. MAIN RESULTS: Classroom temperature and CO2 were assessed every 5 min. Classroom temperatures were 22.4 °C ± 0.1 °C (Day 1) and 26.2 °C ± 0.1 °C (Day 2). Student's thermal comfort was lower during Day 2 compared to Day 1. HR, LF/HF and 0V% were greater during Day 2 (79.5 ± 12.1 bpm, 6.9 ± 7.1 and 32.8% ± 10.3%) than during Day 1 (72.6 ± 10.8 bpm, 3.4 ± 3.7, 21.4% ± 9.2%). Conversely, 2V% was lower during Day 2 (23.1% ± 8.1%) than during Day 1 (32.3% ± 11.4%). Short-term memory, verbal ability and the overall cognitive C-score scores were lower during Day 2 (10.3 ± 0.3; 8.1 ± 1.2 and 10.9 ± 2.0) compared to Day 1 (11.7 ± 2.1; 10.7 ± 1.7 and 12.6 ± 1.8). SIGNIFICANCE: During Day 2, a shift of the cardiac autonomic control towards a sympathetic predominance was observed compared to Day 1, in the presence of greater thermal discomfort. Furthermore, during Day 2 reduced cognitive performances were found.


Subject(s)
Autonomic Nervous System/physiology , Cognition/physiology , Heart/physiology , Students , Temperature , Universities , Electrocardiography , Female , Heart Rate , Humans , Male , Microclimate , Young Adult
3.
Annu Int Conf IEEE Eng Med Biol Soc ; 2019: 6822-6825, 2019 Jul.
Article in English | MEDLINE | ID: mdl-31947407

ABSTRACT

In recent years, there has been a growing interest in video Photoplethysmography (vPPG), a technique able to estimate cardiovascular parameters from video recordings of the skin. Despite the growing interest in vPPG technology, there are still problems in extracting the correct waveform of blood volume pulse, mainly due to real world artifacts, such as changes in light condition and movement artifacts. Another important issue is the correct definition of skin against background. Therefore, we propose an algorithm of skin detection that is able to recognize skin pixels solid to variations of luminosity. We recorded the signals of interest during an experimental protocol designed to provide thermal stimulation and observe the resulting Autonomic Nervous System changes. Experimental data were gathered from 10 young healthy subjects (age: 21±2 years). Video recordings are processed using a band-pass filter and then an automatic algorithm of peak detection is applied to detect the pulse wave peaks, then used to estimate heart rate variability (HRV). The efficiency and stability of the algorithm are compared against finger-PPG waveforms. Preliminary results show an overall statistical agreement between time and frequency domain indexes. However, further efforts are required to improve the estimation of frequency components, particularly during rest.


Subject(s)
Photoplethysmography , Algorithms , Artifacts , Heart Rate , Signal Processing, Computer-Assisted
4.
Annu Int Conf IEEE Eng Med Biol Soc ; 2016: 521-524, 2016 Aug.
Article in English | MEDLINE | ID: mdl-28268384

ABSTRACT

Video photoplethysmography (videoPPG) has emerged as area of great interest thanks to the possibility of remotely assessment of cardiovascular parameters, as heart rate (HR), respiration rate (RR) and heart rate variability (HRV). The present article proposes a fully automated method based on chrominance model, that selects for each subject the best region of interest (ROI) to detect and evaluate the accuracy of beat detection and interbeat intervals (IBI) measurements. The experimental recordings were conducted on 26 subjects which underwent a rest-to-stand maneuver. The results show that the accuracy of beat detection is slightly better during supine position (95%) compared to the standing one (92%), due to the maintenance of the balance that introduces larger motion artifact in the signal dynamic. The error in the measurement (expressed as mean±sd) of instantaneous heart rate is of +0.04 ±3.29 bpm in rest and +0.01±4.26 bpm in stand.


Subject(s)
Heart Function Tests/instrumentation , Heart Rate , Adult , Artifacts , Female , Humans , Male , Photoplethysmography , Rest , Supine Position , Young Adult
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