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Abstract Study Objectives Consumer sleep-tracking devices are widely used and becoming more technologically advanced, creating strong interest from researchers and clinicians for their possible use as alternatives to standard actigraphy. We, therefore, tested the performance of many of the latest consumer sleep-tracking devices, alongside actigraphy, versus the gold-standard sleep assessment technique, polysomnography (PSG). Methods In total, 34 healthy young adults (22 women; 28.1 ± 3.9 years, mean ± SD) were tested on three consecutive nights (including a disrupted sleep condition) in a sleep laboratory with PSG, along with actigraphy (Philips Respironics Actiwatch 2) and a subset of consumer sleep-tracking devices. Altogether, four wearable (Fatigue Science Readiband, Fitbit Alta HR, Garmin Fenix 5S, Garmin Vivosmart 3) and three nonwearable (EarlySense Live, ResMed S+, SleepScore Max) devices were tested. Sleep/wake summary and epoch-by-epoch agreement measures were compared with PSG. Results Most devices (Fatigue Science Readiband, Fitbit Alta HR, EarlySense Live, ResMed S+, SleepScore Max) performed as well as or better than actigraphy on sleep/wake performance measures, while the Garmin devices performed worse. Overall, epoch-by-epoch sensitivity was high (all ≥0.93), specificity was low-to-medium (0.18–0.54), sleep stage comparisons were mixed, and devices tended to perform worse on nights with poorer/disrupted sleep. Conclusions Consumer sleep-tracking devices exhibited high performance in detecting sleep, and most performed equivalent to (or better than) actigraphy in detecting wake. Device sleep stage assessments were inconsistent. Findings indicate that many newer sleep-tracking devices demonstrate promising performance for tracking sleep and wake. Devices should be tested in different populations and settings to further examine their wider validity and utility.

Laser‐based noncontact precision metrology has become indispensable in advanced manufacturing, semiconductor inspection, biomedical engineering, and structural health monitoring. This review critically evaluates the evolution and integration of laser measurement systems with state‐of‐the‐art imaging technologies, emphasizing their roles in achieving submicron accuracy, high scanning speeds, and real‐time adaptability. Foundational techniques such as laser triangulation and interferometry are reassessed in terms of their spatial resolution, susceptibility to ambient noise, and scalability for large or complex surfaces. Emerging optical approaches, namely, adaptive optics (AO), time‐of‐flight (ToF) sensors, confocal microscopy, and digital holography are examined for their capability to enhance depth precision, reduce scattering effects, and compensate for wavefront distortions. The application of quantum metrology introduces novel paradigms in precision measurement, utilizing entangled photon states and quantum correlations to exceed classical sensitivity limits. Building Information Modeling (BIM) integration enables the fusion of geometric data with laser scan outputs, facilitating digital twin development and predictive analytics for structural maintenance. The paper also highlights the rising role of artificial intelligence (AI) and machine learning (ML) in metrology systems, offering solutions for noise filtration, surface anomaly detection, and adaptive calibration. Operational challenges such as thermal drift, environmental vibrations, and data bottlenecks are discussed alongside mitigation strategies including sensor fusion and real‐time digital compensation.

Heart rate (HR) is one of the essential vital signs used to indicate the physiological health of the human body. While traditional HR monitors usually require contact with skin, remote photoplethysmography (rPPG) enables contactless HR monitoring by capturing subtle light changes of skin through a video camera. Given the vast potential of this technology in the future of digital healthcare, remote monitoring of physiological signals has gained significant traction in the research community. In recent years, the success of deep learning (DL) methods for image and video analysis has inspired researchers to apply such techniques to various parts of the remote physiological signal extraction pipeline. In this paper, we discuss several recent advances of DL-based methods specifically for remote HR measurement, categorizing them based on model architecture and application. We further detail relevant real-world applications of remote physiological monitoring and summarize various common resources used to accelerate related research progress. Lastly, we analyze the implications of research findings and discuss research gaps to guide future explorations.

In recent years, noncontact measurements of vital signs using cameras received a great amount of interest. However, some questions are unanswered: (i) Which vital sign is monitored using what type of camera? (ii) What is the performance and which factors affect it? (iii) Which health issues are addressed by camera-based techniques? Following the preferred reporting items for systematic reviews and meta-analyses (PRISMA) statement, we conduct a systematic review of continuous camera-based vital sign monitoring using Scopus, PubMed, and the Association for Computing Machinery (ACM) databases. We consider articles that were published between January 2018 and April 2021 in the English language. We include five vital signs: heart rate (HR), respiratory rate (RR), blood pressure (BP), body skin temperature (BST), and oxygen saturation (SpO2). In total, we retrieve 905 articles and screened them regarding title, abstract, and full text. One hundred and four articles remained: 60, 20, 6, 2, and 1 of the articles focus on HR, RR, BP, BST, and SpO2, respectively, and 15 on multiple vital signs. HR and RR can be measured using red, green, and blue (RGB) and near-infrared (NIR) as well as far-infrared (FIR) cameras. So far, BP and SpO2 are monitored with RGB cameras only, whereas BST is derived from FIR cameras only. Under ideal conditions, the root mean squared error is around 2.60 bpm, 2.22 cpm, 6.91 mm Hg, 4.88 mm Hg, and 0.86 °C for HR, RR, systolic BP, diastolic BP, and BST, respectively. The estimated error for SpO2 is less than 1%, but it increases with movements of the subject and the camera-subject distance. Camera-based remote monitoring mainly explores intensive care, post-anaesthesia care, and sleep monitoring, but also explores special diseases such as heart failure. The monitored targets are newborn and pediatric patients, geriatric patients, athletes (e.g., exercising, cycling), and vehicle drivers. Camera-based techniques monitor HR, RR, and BST in static conditions within acceptable ranges for certain applications. The research gaps are large and heterogeneous populations, real-time scenarios, moving subjects, and accuracy of BP and SpO2 monitoring.

HighlightsThis report summarizes recent advances of flexible humidity sensors and their integrated systems.Typical examples of noncontact detections based on flexible and wearable humidity sensors are highlighted.Research opportunities and challenges of pushing flexible humidity sensors towards practical contactless measurements are discussed.In the past decade, the global industry and research attentions on intelligent skin-like electronics have boosted their applications in diverse fields including human healthcare, Internet of Things, human–machine interfaces, artificial intelligence and soft robotics. Among them, flexible humidity sensors play a vital role in noncontact measurements relying on the unique property of rapid response to humidity change. This work presents an overview of recent advances in flexible humidity sensors using various active functional materials for contactless monitoring. Four categories of humidity sensors are highlighted based on resistive, capacitive, impedance-type and voltage-type working mechanisms. Furthermore, typical strategies including chemical doping, structural design and Joule heating are introduced to enhance the performance of humidity sensors. Drawing on the noncontact perception capability, human/plant healthcare management, human–machine interactions as well as integrated humidity sensor-based feedback systems are presented. The burgeoning innovations in this research field will benefit human society, especially during the COVID-19 epidemic, where cross-infection should be averted and contactless sensation is highly desired.

This paper reports the noncontact manipulation of free-falling cylindrical streams of liquid metals into unique shapes, such as levitated loops and squares. Such cylindrical streams form in aqueous media by electrochemically lowering the interfacial tension. The electrochemical reactions require an electrical current that flows through the streams, making them susceptible to the Lorentz force. Consequently, varying the position and shape of a magnetic field relative to the stream controls these forces. Moreover, the movement of the metal stream relative to the magnetic field induces significant forces arising from Lenz’s law that cause the manipulated streams to levitate in unique shapes. The ability to control streams of liquid metals in a noncontact manner will enable strategies for shaping electronically conductive fluids for advanced manufacturing and dynamic electronic structures.

In this paper, we compare the performances of impulse radio ultra-wideband (IR-UWB) and frequency modulation continuous wave (FMCW) radars in measuring noncontact vital signs such as respiration rate and heart rate. These two type radars have been widely used in various fields and have shown their applicability to extract vital signs in noncontact ways. IR-UWB radar can extract vital signs using distance information. On the other hand, FMCW radar requires phase information to estimate vital signs, and the result can be enhanced with Multi-input Multi-output (MIMO) antenna topologies. By using commercial radar chipsets, the operation of radars under different conditions and frequency bands will also affect the performance of vital sign detection capabilities. We compared the accuracy and signal-to-noise (SNR) ratios of IR-UWB and FMCW radars in various scenarios, such as distance, orientation, carotid pulse, harmonics, and obstacle penetration. In general, the IR-UWB radars offer a slightly better accuracy and higher SNR in comparison to FMCW radar. However, each radar system has its own unique advantages, with IR-UWB exhibiting fewer harmonics and a higher SNR, while FMCW can combine the results from each channel.

Purpose: Intraocular pressure (IOP) measurement is critical in diagnosing and managing eye conditions. This study aims to assess the comparability of three alternative devices for measuring IOP: Noncontact tonometer, Icare rebound tonometer, and Tono-Pen. Patients and Methods: A cross-sectional study included 172 adult participants (87 males and 85 females) who underwent IOP and central corneal thickness (CCT) assessments. IOP was measured using Noncontact (Canon TX-20), Icare (Icare TA01i), and Tono-Pen (Tonopen XL). CCT was measured with the built-in pachymetry of the Noncontact tonometer. Correlation coefficients and Bland-Altman analyses were conducted to assess the relationships and agreements between these tonometers. Participants were grouped based on IOP and CCT levels. The mean of the standard deviation of the three tonometer results was calculated to evaluate measurement result variability. One-way analysis of variance was conducted for comparing between the groups. Results: IOP measurements among the three devices were not significantly different, indicating their comparability. Correlation analysis revealed strong correlations between the tonometers. Bland-Altman analysis showed good agreement, with the Icare rebound tonometer and Tono-Pen exhibiting narrower limits of agreement. Furthermore, IOP levels influenced measurement result variability, with higher IOP levels associated with greater variance. Conclusion: This study demonstrates that the alternative devices examined can provide reliable IOP measurements. It highlights the potential of these alternative devices for IOP measurement. These findings have implications for clinical practice, offering practitioners additional tools for accurate IOP assessment. Keywords: intraocular pressure, tonometer, noncontact, icare, Tono-Pen

Significance: Non-contact, camera-based heart rate variability estimation is desirable in numerous applications, including medical, automotive, and entertainment. Unfortunately, camera-based HRV accuracy and reliability suffer due to two challenges: (a) darker skin tones result in lower SNR and (b) relative motion induces measurement artifacts. Aim: We propose an algorithm HRVCam that provides sufficient robustness to low SNR and motion-induced artifacts commonly present in imaging photoplethysmography (iPPG) signals. Approach: HRVCam computes camera-based HRV from the instantaneous frequency of the iPPG signal. HRVCam uses automatic adaptive bandwidth filtering along with discrete energy separation to estimate the instantaneous frequency. The parameters of HRVCam use the observed characteristics of HRV and iPPG signals. Results: We capture a new dataset containing 16 participants with diverse skin tones. We demonstrate that HRVCam reduces the error in camera-based HRV metrics significantly (more than 50% reduction) for videos with dark skin and face motion. Conclusion: HRVCam can be used on top of iPPG estimation algorithms to provide robust HRV measurements making camera-based HRV practical.

There is considerable interest in the noncontact monitoring of patients as it allows for reduced restriction of patients, the avoidance of single-use consumables and less patient–clinician contact and hence the reduction of the spread of disease. A technology that has come to the fore for noncontact respiratory monitoring is that based on depth sensing camera systems. This has great potential for the monitoring of a range of respiratory information including the provision of a respiratory waveform, the calculation of respiratory rate and tidal volume (and hence minute volume). Respiratory patterns and apneas can also be observed in the signal. Here we review the ability of this method to provide accurate and clinically useful respiratory information.