Research

20 pages, 7670 KiB

Open AccessEditor’s ChoiceArticle

A Novel Non-Contact Detection and Identification Method for the Post-Disaster Compression State of Injured Individuals Using UWB Bio-Radar

by Ding Shi, Fulai Liang, Jiahao Qiao, Yaru Wang, Yidan Zhu, Hao Lv, Xiao Yu, Teng Jiao, Fuyuan Liao, Keding Yan, Jianqi Wang and Yang Zhang

Bioengineering 2023, 10(8), 905; https://doi.org/10.3390/bioengineering10080905 - 30 Jul 2023

Cited by 1 | Viewed by 1201

Abstract

Building collapse leads to mechanical injury, which is the main cause of injury and death, with crush syndrome as its most common complication. During the post-disaster search and rescue phase, if rescue personnel hastily remove heavy objects covering the bodies of injured individuals [...] Read more.

Building collapse leads to mechanical injury, which is the main cause of injury and death, with crush syndrome as its most common complication. During the post-disaster search and rescue phase, if rescue personnel hastily remove heavy objects covering the bodies of injured individuals and fail to provide targeted medical care, ischemia-reperfusion injury may be triggered, leading to rhabdomyolysis. This may result in disseminated intravascular coagulation or acute respiratory distress syndrome, further leading to multiple organ failure, which ultimately leads to shock and death. Using bio-radar to detect vital signs and identify compression states can effectively reduce casualties during the search for missing persons behind obstacles. A time-domain ultra-wideband (UWB) bio-radar was applied for the non-contact detection of human vital sign signals behind obstacles. An echo denoising algorithm based on PSO-VMD and permutation entropy was proposed to suppress environmental noise, along with a wounded compression state recognition network based on radar-life signals. Based on training and testing using over 3000 data sets from 10 subjects in different compression states, the proposed multiscale convolutional network achieved a 92.63% identification accuracy. This outperformed SVM and 1D-CNN models by 5.30% and 6.12%, respectively, improving the casualty rescue success and post-disaster precision. Full article

(This article belongs to the Special Issue Contactless Technologies for Human Vital Signs Monitoring)

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15 pages, 5195 KiB

Open AccessArticle

Robust Heart Rate Variability Measurement from Facial Videos

by Ismoil Odinaev, Kwan Long Wong, Jing Wei Chin, Raghav Goyal, Tsz Tai Chan and Richard H. Y. So

Bioengineering 2023, 10(7), 851; https://doi.org/10.3390/bioengineering10070851 - 18 Jul 2023

Cited by 2 | Viewed by 1798

Abstract

Remote Photoplethysmography (rPPG) is a contactless method that enables the detection of various physiological signals from facial videos. rPPG utilizes a digital camera to detect subtle changes in skin color to measure vital signs such as heart rate variability (HRV), an important biomarker [...] Read more.

Remote Photoplethysmography (rPPG) is a contactless method that enables the detection of various physiological signals from facial videos. rPPG utilizes a digital camera to detect subtle changes in skin color to measure vital signs such as heart rate variability (HRV), an important biomarker related to the autonomous nervous system. This paper presents a novel contactless HRV extraction algorithm, WaveHRV, based on the Wavelet Scattering Transform technique, followed by adaptive bandpass filtering and inter-beat-interval (IBI) analysis. Furthermore, a novel method is introduced to preprocess noisy contact-based PPG signals. WaveHRV is bench-marked against existing algorithms and public datasets. Our results show that WaveHRV is promising and achieves the lowest mean absolute error (MAE) of 10.5 ms and 6.15 ms for RMSSD and SDNN on the UBFCrPPG dataset. Full article

(This article belongs to the Special Issue Contactless Technologies for Human Vital Signs Monitoring)

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10 pages, 1135 KiB

Open AccessArticle

Infrared Thermography Imaging for Assessment of Peripheral Perfusion in Patients with Septic Shock

by Sigita Kazune, Edgars Vasiljevs, Anastasija Caica-Rinca, Zbignevs Marcinkevics and Andris Grabovskis

Bioengineering 2023, 10(6), 729; https://doi.org/10.3390/bioengineering10060729 - 18 Jun 2023

Cited by 1 | Viewed by 1112

Abstract

Skin temperature changes can be used to assess peripheral perfusion in circulatory shock patients. However, research has been limited to point measurements from acral parts of the body. Infrared thermography allows non-invasive evaluation of temperature distribution over a larger surface. Our study aimed [...] Read more.

Skin temperature changes can be used to assess peripheral perfusion in circulatory shock patients. However, research has been limited to point measurements from acral parts of the body. Infrared thermography allows non-invasive evaluation of temperature distribution over a larger surface. Our study aimed to map thermographic patterns in the knee and upper thigh of 81 septic shock patients within 24 h of admission and determine the relationship between skin temperature patterns, mottling, and 28-day mortality. We extracted skin temperature measurements from zones corresponding to mottling scores and used a linear mixed model to analyze the distribution of skin temperature in patients with different mottling scores. Our results showed that the distribution of skin temperature in the anterior thigh and knee is physiologically heterogeneous and has no significant association with mottling or survival at 28 days. However, overall skin temperature of the anterior thigh and knee is significantly lower in non-survivors when modified by mottling score. No differences were found in skin temperature between the survivor and non-survivor groups. Our study shows the potential usefulness of infrared thermography in evaluating skin temperature patterns in resuscitated septic shock patients. Overall skin temperature of the anterior thigh and knee may be an important indicator of survival status when modified by mottling score. Full article

(This article belongs to the Special Issue Contactless Technologies for Human Vital Signs Monitoring)

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17 pages, 5034 KiB

Open AccessArticle

For Heart Rate Assessments from Drone Footage in Disaster Scenarios

by Lucas Mösch, Isabelle Barz, Anna Müller, Carina B. Pereira, Dieter Moormann, Michael Czaplik and Andreas Follmann

Bioengineering 2023, 10(3), 336; https://doi.org/10.3390/bioengineering10030336 - 07 Mar 2023

Cited by 2 | Viewed by 1527

Abstract

The ability to use drones to obtain important vital signs could be very valuable for emergency personnel during mass-casualty incidents. The rapid and robust remote assessment of heart rates could serve as a life-saving decision aid for first-responders. With the flight sensor data [...] Read more.

The ability to use drones to obtain important vital signs could be very valuable for emergency personnel during mass-casualty incidents. The rapid and robust remote assessment of heart rates could serve as a life-saving decision aid for first-responders. With the flight sensor data of a specialized drone, a pipeline was developed to achieve a robust, non-contact assessment of heart rates through remote photoplethysmography (rPPG). This robust assessment was achieved through adaptive face-aware exposure and comprehensive de-noising of a large number of predicted noise sources. In addition, we performed a proof-of-concept study that involved 18 stationary subjects with clean skin and 36 recordings of their vital signs, using the developed pipeline in outdoor conditions. In this study, we could achieve a single-value heart-rate assessment with an overall root-mean-squared error of 14.3 beats-per-minute, demonstrating the basic feasibility of our approach. However, further research is needed to verify the applicability of our approach in actual disaster situations, where remote photoplethysmography readings could be impacted by other factors, such as blood, dirt, and body positioning. Full article

(This article belongs to the Special Issue Contactless Technologies for Human Vital Signs Monitoring)

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22 pages, 11117 KiB

Open AccessArticle

WiFi-Based Detection of Human Subtle Motion for Health Applications

by Hui-Hsin Chen, Chi-Lun Lin and Chun-Hsiang Chang

Bioengineering 2023, 10(2), 228; https://doi.org/10.3390/bioengineering10020228 - 08 Feb 2023

Cited by 3 | Viewed by 2583

Abstract

Neurodegenerative diseases such as Parkinson’s disease affect motor symptoms with abnormally increased or reduced movements. Symptoms such as tremor and hand movement disorders can be subtle and vary daily such that the actual condition of the disease may not fully present in clinical [...] Read more.

Neurodegenerative diseases such as Parkinson’s disease affect motor symptoms with abnormally increased or reduced movements. Symptoms such as tremor and hand movement disorders can be subtle and vary daily such that the actual condition of the disease may not fully present in clinical sessions. Health examination and monitoring, if available in the living space, can capture comprehensive and quantitative information about a patient’s motor symptoms, allowing physicians to make a precise diagnosis and devise a more personalized treatment. WiFi-based sensing is a potential solution for passively detecting human motion in a contactless way that collects no personally identifiable information. This study proposed an approach for human micromotion detection using the WiFi channel state information, which can be realized in a regular-sized room for home health monitoring and examination. Three types of motion were tested to evaluate the proposed method in quantifying micromotion using single and multiple WiFi links. The results show that micromotion could be captured at all distributed locations in the experimental environment (4.2 m × 7.9 m). Our computer algorithm computed the frequency and duration of simulated hand tremors with an average accuracy of 90.9% (single WiFi link)—95.7% (multiple WiFi links). Full article

(This article belongs to the Special Issue Contactless Technologies for Human Vital Signs Monitoring)

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17 pages, 11842 KiB

Open AccessArticle

Contactless Stethoscope Enabled by Radar Technology

by Isabella Lenz, Yu Rong and Daniel Bliss

Bioengineering 2023, 10(2), 169; https://doi.org/10.3390/bioengineering10020169 - 28 Jan 2023

Cited by 7 | Viewed by 1745

Abstract

Contactless vital sign measurement technologies have the potential to greatly improve patient experiences and practitioner safety while creating the opportunity for comfortable continuous monitoring. We introduce a contactless alternative for measuring human heart sounds. We leverage millimeter wave frequency-modulated continuous wave radar and [...] Read more.

Contactless vital sign measurement technologies have the potential to greatly improve patient experiences and practitioner safety while creating the opportunity for comfortable continuous monitoring. We introduce a contactless alternative for measuring human heart sounds. We leverage millimeter wave frequency-modulated continuous wave radar and multi-input multi-output beamforming techniques to capture fine skin vibrations that result from the cardiac movements that cause heart sounds. We discuss contact-based heart sound measurement techniques and directly compare the radar heart sound technique with these contact-based approaches. We present experimental cases to test the strengths and limitations of both the contact-based measurement techniques and the contactless radar measurement. We demonstrate that the radar measurement technique is a viable and potentially superior method for capturing human heart sounds in many practical settings. Full article

(This article belongs to the Special Issue Contactless Technologies for Human Vital Signs Monitoring)

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14 pages, 1580 KiB

Open AccessEditor’s ChoiceArticle

Contactless Camera-Based Sleep Staging: The HealthBed Study

by Fokke B. van Meulen, Angela Grassi, Leonie van den Heuvel, Sebastiaan Overeem, Merel M. van Gilst, Johannes P. van Dijk, Henning Maass, Mark J. H. van Gastel and Pedro Fonseca

Bioengineering 2023, 10(1), 109; https://doi.org/10.3390/bioengineering10010109 - 12 Jan 2023

Cited by 11 | Viewed by 2197

Abstract

Polysomnography (PSG) remains the gold standard for sleep monitoring but is obtrusive in nature. Advances in camera sensor technology and data analysis techniques enable contactless monitoring of heart rate variability (HRV). In turn, this may allow remote assessment of sleep stages, as different [...] Read more.

Polysomnography (PSG) remains the gold standard for sleep monitoring but is obtrusive in nature. Advances in camera sensor technology and data analysis techniques enable contactless monitoring of heart rate variability (HRV). In turn, this may allow remote assessment of sleep stages, as different HRV metrics indirectly reflect the expression of sleep stages. We evaluated a camera-based remote photoplethysmography (PPG) setup to perform automated classification of sleep stages in near darkness. Based on the contactless measurement of pulse rate variability, we use a previously developed HRV-based algorithm for 3 and 4-class sleep stage classification. Performance was evaluated on data of 46 healthy participants obtained from simultaneous overnight recording of PSG and camera-based remote PPG. To validate the results and for benchmarking purposes, the same algorithm was used to classify sleep stages based on the corresponding ECG data. Compared to manually scored PSG, the remote PPG-based algorithm achieved moderate agreement on both 3 class (Wake–N1/N2/N3–REM) and 4 class (Wake–N1/N2–N3–REM) classification, with average

κ

of 0.58 and 0.49 and accuracy of 81% and 68%, respectively. This is in range with other performance metrics reported on sensing technologies for wearable sleep staging, showing the potential of video-based non-contact sleep staging. Full article

(This article belongs to the Special Issue Contactless Technologies for Human Vital Signs Monitoring)

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10 pages, 2795 KiB

Open AccessArticle

Comparing Remote Speckle Plethysmography and Finger-Clip Photoplethysmography with Non-Invasive Finger Arterial Pressure Pulse Waves, Regarding Morphology and Arrival Time

by Jorge Herranz Olazabal, Fokko Wieringa, Evelien Hermeling and Chris Van Hoof

Bioengineering 2023, 10(1), 101; https://doi.org/10.3390/bioengineering10010101 - 11 Jan 2023

Cited by 4 | Viewed by 2246

Abstract

Objective: The goal was to compare Speckle plethysmography (SPG) and Photoplethysmography (PPG) with non-invasive finger Arterial Pressure (fiAP) regarding Pulse Wave Morphology (PWM) and Pulse Arrival Time (PAT). Methods: Healthy volunteers (n = 8) were connected to a Non-Invasive Blood Pressure (NIBP) monitor [...] Read more.

Objective: The goal was to compare Speckle plethysmography (SPG) and Photoplethysmography (PPG) with non-invasive finger Arterial Pressure (fiAP) regarding Pulse Wave Morphology (PWM) and Pulse Arrival Time (PAT). Methods: Healthy volunteers (n = 8) were connected to a Non-Invasive Blood Pressure (NIBP) monitor providing fiAP pulse wave and PPG from a clinical transmission-mode SpO₂ finger clip. Biopac recorded 3-lead ECG. A camera placed at a 25 cm distance recorded a video stream (100 fps) of a finger illuminated by a laser diode at 639 nm. A chest belt (Polar) monitored respiration. All signals were recorded simultaneously during episodes of spontaneous breathing and paced breathing. Analysis: Post-processing was performed in Matlab to obtain SPG and analyze the SPG, PPG and fiAP mean absolute deviations (MADs) on PWM, plus PAT modulation. Results: Across 2599 beats, the average fiAP MAD with PPG was 0.17 (0–1) and with SPG 0.09 (0–1). PAT derived from ECG–fiAP correlated as follows: 0.65 for ECG–SPG and 0.67 for ECG–PPG. Conclusion: Compared to the clinical NIBP monitor fiAP reference, PWM from an experimental camera-derived non-contact reflective-mode SPG setup resembled fiAP significantly better than PPG from a simultaneously recorded clinical transmission-mode finger clip. For PAT values, no significant difference was found between ECG–SPG and ECG–PPG compared to ECG–fiAP. Full article

(This article belongs to the Special Issue Contactless Technologies for Human Vital Signs Monitoring)

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