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Breast cancers can appear and progress rapidly, necessitating more frequent monitoring outside of hospital settings to significantly reduce mortality rates. Recently, there has been considerable interest in developing techniques for portable, user-friendly, and low-cost breast tumor monitoring applications, enabling frequent and cost-efficient examinations. Microwave technique-based breast cancer detection, which is based on differential dielectric properties of malignant and healthy tissues, is regarded as a promising solution for cost-effective breast tumor monitoring. This paper presents the development process of the first proof-of-concept of a breast tumor monitoring vest which is based on the microwave technique. Two unique vests are designed and evaluated on realistic 3D human tissue phantoms having different breast density types. Additionally, the measured results are verified using simulations carried out on anatomically realistic voxel models of the electromagnetic simulations. The radio channel characteristics are evaluated and analyzed between the antennas embedded in the vest in tumor cases and reference cases. Both measurements and simulation results show that the proposed vest can detect tumors even if only 1 cm in diameter. Additionally, simulation results show detectability with 0.5 cm tumors. It is observed that the detectability of breast tumors depends on the frequency, antenna selection, size of the tumors, and breast types, causing differences of 0.5-30 dB in channel responses between the tumorous and reference cases. Due to simplicity and cost-efficiency, the proposed channel analysis-based breast monitoring vests can be used for breast health checks in smaller healthcare centers and for user-friendly home monitoring which can prove beneficial in rural areas and developing countries.

(1) Objective: This study aims to lay a foundation for noncontact intensive care monitoring of premature babies. (2) Methods: Arterial oxygen saturation and heart rate were measured using a monochrome camera and time-division multiplex controlled lighting at three different wavelengths (660 nm, 810 nm and 940 nm) on a piglet model. (3) Results: Using this camera system and our newly designed algorithm for further analysis, the detection of a heartbeat and the calculation of oxygen saturation were evaluated. In motionless individuals, heartbeat and respiration were separated clearly during light breathing and with only minor intervention. In this case, the mean difference between noncontact and contact saturation measurements was 0.7% (RMSE = 3.8%, MAE = 2.93%). (4) Conclusions: The new sensor was proven effective under ideal animal experimental conditions. The results allow a systematic improvement for the further development of contactless vital sign monitoring systems. The results presented here are a major step towards the development of an incubator with noncontact sensor systems for use in the neonatal intensive care unit.

In recent years, the interest in medical monitoring for human health has been rapidly increasing due to widespread concern. Hydrogels are widely used in medical monitoring and other fields due to their excellent mechanical properties, electrical conductivity and adhesion. However, some of the non-degradable materials in hydrogels may cause some environmental damage and resource waste. Therefore, organic renewable natural polymers with excellent properties of biocompatibility, biodegradability, low cost and non-toxicity are expected to serve as an alternative to those non-degradable materials, and also provide a broad application prospect for the development of natural-polymer-based hydrogels as flexible electronic devices. This paper reviews the progress of research on many different types of natural-polymer-based hydrogels such as proteins and polysaccharides. The applications of natural-polymer-based hydrogels in body movement detection and biomedical monitoring are then discussed. Finally, the present challenges and future prospects of natural polymer-based hydrogels are summarized.

Objective: To develop a new method of evaluating swallowing behaviour., Methods: Sixty-nine healthy participants were divided into a younger (16 males and 16 females, mean age 39.09 ± 12.16 years) and older (18 males and 19 females, mean age 71.43 ± 5.50 years) group. The participants ingested water and yoghurt twice (directed and free swallowing) at rest and after performing simple daily life tasks (calculation and exercise). To measure swallowing frequency, we employed a smartphone-based, portable and neck-worn swallowing-sound-monitoring device. This device monitors swallowing behaviour continuously by collecting biological sounds from the neck without imposing behavioural restrictions. A neural network model of swallowing sound identification by deep learning was used for the subsequent evaluation. This device was used to obtain two types of saliva-swallowing sounds associated with different ingestants, at rest and after performing a stimulating task. Furthermore, we assessed the associated subjective psychological states., Results: The younger group showed a higher directed swallowing frequency (for both water and yoghurt) than the older group did. Regarding the type of ingestant, the swallowing frequency for yoghurt was higher during free swallowing in both the young and the older groups. 'Feeling calm' was reported significantly more often in the older group after swallowing yoghurt following exercise., Conclusions: Swallowing status in daily life was measured non-invasively using a wearable mobile device. It is important to consider the type of ingestant, daily living activities, and age when assessing swallowing., Competing Interests: This study was jointly performed by the National Center for Geriatrics and Gerontology, PLIMES Inc, and Meiji Co, Ltd. YT holds the position of joint research chair, and MT is a leading researcher in joint research. MT, SM, and TS received funding from Meiji Co, Ltd for this study. TH and YT are employees of Meiji Co, Ltd, which provided the yoghurt used in this study. ST and KS declare no competing interests., (© The Author(s) 2024.)

In biomedical monitoring, non-intrusive and continuous tracking of vital signs is a crucial yet challenging objective. Although accurate, traditional methods, such as electrocardiography (ECG) and photoplethysmography (PPG), necessitate direct contact with the patient, posing limitations for long-term and unobtrusive monitoring. To address this challenge, we introduce the EmRad system, an innovative solution harnessing the capabilities of continuous-wave (CW) radar technology for the contactless detection of vital signs, including heart rate and respiratory rate. EmRad discerns itself by emphasizing miniaturization, performance, scalability, and its ability to generate large-scale datasets in various environments. This article explains the system's design, focusing on signal processing strategies and motion artifact reduction to ensure precise vital sign extraction. The EmRad system's versatility is showcased through various case studies, highlighting its potential to transform vital sign monitoring in research and clinical contexts., Competing Interests: The authors have no conflicts of interest to declare., (© 2024 The Authors.)

This manuscript explores the transformative potential of swellable microneedles (MNs) in drug delivery and diagnostics, addressing critical needs in medical treatment and monitoring. Innovations in hydrogel-integrated MN arrays facilitate controlled drug release, thereby expanding treatment options for chronic diseases and conditions that require precise dosage control. The review covers challenges, such as scalability, patient compliance, and manufacturing processes, as well as achievements in advanced manufacturing, biocompatibility, and versatile applications. Nonetheless, limitations in physiological responsiveness and long-term stability remain, necessitating further research in material innovation and integration with digital technologies. Future directions focus on expanding biomedical applications, material advancements, and regulatory considerations for widespread clinical adoption.

Radio detection and ranging-based (radar) sensing offers unique opportunities for biomedical monitoring and can help overcome the limitations of currently established solutions. Due to its contactless and unobtrusive measurement principle, it can facilitate the longitudinal recording of human physiology and can help to bridge the gap from laboratory to real-world assessments. However, radar sensors typically yield complex and multidimensional data that are hard to interpret without domain expertise. Machine learning (ML) algorithms can be trained to extract meaningful information from radar data for medical experts, enhancing not only diagnostic capabilities but also contributing to advancements in disease prevention and treatment. However, until now, the two aspects of radar-based data acquisition and ML-based data processing have mostly been addressed individually and not as part of a holistic and end-to-end data analysis pipeline. For this reason, we present a tutorial on radar-based ML applications for biomedical monitoring that equally emphasizes both dimensions. We highlight the fundamentals of radar and ML theory, data acquisition and representation and outline categories of clinical relevance. Since the contactless and unobtrusive nature of radar-based sensing also raises novel ethical concerns regarding biomedical monitoring, we additionally present a discussion that carefully addresses the ethical aspects of this novel technology, particularly regarding data privacy, ownership, and potential biases in ML algorithms., Competing Interests: The authors declare that they have no commercial or financial relationships that could be construed as a potential conflict of interest., (© 2024 The Authors.)

Long-term daily-life body signal monitoring offers numerous advantages, such as timely response to health alerts, diseases monitoring, and reducing time and expenses related to clinical trials. Access to physiological data can be achieved with low-cost and comfortable wireless wearable sensors. In our previous publication, we reported a low-cost, easy to implement, and unobtrusive wireless resistive analog passive (WRAP) sensor to provide a feasible bio-signal monitoring technique by using a pair of printed spiral coils (PSC) in a near field connection. Sensitivity, defined as the response to the transducer, is a critical feature in the establishment of a reliable system. In the previous publication, we presented the utilization of a Genetic Algorithm to design a pair of coils and related components to maximize sensitivity. Although the coils' misalignment can significantly affect the optimized sensitivity, it was not incorporated into the optimization process. This paper focuses on optimizing the coils and components in order to maximize both their sensitivity and their resilience against movements of the PSC pair. In a square-shaped pair comprising a primary coil of 60 mm and a secondary coil of 20 mm dimensions, we found that the sensitivity is maximized at 1.3 mƱ for a 16 mm axial distance. Additionally, it remains above 0.65 mƱ within ±11.25 mm lateral and +14 mm axial displacements.

Due to the high heterogeneity in outcome measures after total hip arthroplasty (THA), the prospective observational study investigated the relationships between symmetry-based (SBMs), performance-based (PBMs), and functional outcome measures in THA patients to determine necessary or redundant categories of tests. The study material consisted of 24 patients with end-stage hip osteoarthritis scheduled for THA. The patients were examined one day before surgery and consecutively on the 4th day, 9th day, and 10th week postoperatively using the SBMs (weight-bearing chair-rising test, measurements of the maximal isometric torque of the quadriceps muscle); the PBMs (10-m walk, timed up-and-go, and stair-climbing tests); and the functional outcome measure (Harris Hip Score). The results obtained in a given category of tests at different time points were compared, and the correlations between the tests were determined. The reliability of the outcome measures was determined. The results of tests in the studied categories statistically significantly ( p < 0.05) improved at the 10th week postoperatively compared to preoperative results. No strong correlations were revealed between the three studied types of outcome measures in THA patients. Therefore, none of them can be considered redundant. It also means that the relevance of symmetry for a core measurement set to describe the domain function in THA patients must be further clarified.

Cardiovascular diseases kill 18 million people each year. Currently, a patient's health is assessed only during clinical visits, which are often infrequent and provide little information on the person's health during daily life. Advances in mobile health technologies have allowed for the continuous monitoring of indicators of health and mobility during daily life by wearable and other devices. The ability to obtain such longitudinal, clinically relevant measurements could enhance the prevention, detection and treatment of cardiovascular diseases. This review discusses the advantages and disadvantages of various methods for monitoring patients with cardiovascular disease during daily life using wearable devices. We specifically discuss three distinct monitoring domains: physical activity monitoring, indoor home monitoring and physiological parameter monitoring.

Technological advancements are enabling new applications within biomedical engineering. As a connection point between the outer environment and the human system, the oral cavity offers unique opportunities for sensing technologies. This paper systematically reviews the performance of measurement systems tested in the human oral cavity. Performance was defined by metrics related to accuracy and agreement estimation. A comprehensive search identifying human studies that reported on the accuracy or agreement of intraoral sensors found 85 research papers. Most of the literature (62%) was in dentistry, followed by neurology (21%), and physical medicine and rehabilitation (12%). The remaining papers were on internal medicine, obstetrics, and aerospace medicine. Most of the studies applied force or pressure sensors (32%), while optical and image sensors were applied most widely across fields. The main challenges for future adoption include the lack of large human trials, the maturity of emerging technologies (e.g., biochemical sensors), and the absence of standardization of evaluation in specific fields. New research should aim to employ robust performance metrics to evaluate their systems and incorporate real-world evidence as part of the evaluation process. Oral cavity sensors offer the potential for applications in healthcare and wellbeing, but for many technologies, more research is needed.

This pilot study aimed to determine the reliability of a newly developed ultrasound-based protocol for the assessment of patella diameter and sulcus angle. The diameter of the patella expressed in mm and the sulcus angle, expressed in degrees were measured in the right knee in 12 healthy participants (eight women and four men) in two separate sessions by two examiners (experienced rater and inexperienced rater) using ultrasonography according to a developed standardized protocol. The reliability was determined on the calculated intraclass correlation coefficient, ICC, expressed as a 95% confidence interval (lower bound, upper bound). For the patella diameter measurement, intra-rater and inter-rater reliability were good to excellent, with the ICC exceeding 0.836-0.998 and 0.859-0.997, respectively. The intra-rater and inter-rater reliability of the sulcus measurement was moderate to excellent, as the ICC amounted to 0.559-0.993 and 0.559-0.990, respectively. The reliability of both measures increased with the experience of the examiner. Therefore, it was determined that the newly developed protocol for an ultrasound-based assessment of patella diameter and sulcus angle is reliable. Further studies validating their clinical use should be carried out., Competing Interests: The authors declare no conflict of interest.

Joint position sense (JPS) is the awareness of joint location in space, indicating accuracy and precision of the movement. Therefore, the aim of the present study is to determine the reliability of active and passive JPS assessment regarding the knee joint. This was carried out using the Luna EMG rehabilitation robot. Further analysis assessed whether the examination of only the dominant site is justified and if there are differences between sites. The study comprised 24 healthy male participants aged 24.13 ± 2.82 years, performing sports at a recreational level. Using the Luna EMG rehabilitation robot, JPS tests were performed for the right and left knees during flexion and extension in active and passive mode, in two separate sessions with a 1-week interval. Both knee flexion and extension in active and passive modes demonstrated high reliability (ICC = 0.866-0.982; SEM = 0.63-0.31). The mean JPS angle error did not differ significantly between the right and left lower limbs ( p < 0.05); however, no between-limb correlation was noted ( r = 0.21-0.34; p > 0.05). The Bland-Altman plots showed that the between-limb bias was minimal, with relatively wide limits of agreement. Therefore, it was concluded that the Luna EMG rehabilitation robot is a reliable tool for active and passive knee JPS assessment. In our study, JPS angle error did not differ significantly between left and right sides; however, the slight asymmetry was observed (visible in broad level of agreement exceeding 5° in Bland-Altman plots), what may suggest that in healthy subjects, e.g., active athletes, proprioception should always be assessed on both sides.

Background: The quest for improved diagnosis and treatment in home health care models has led to the development of wearable medical devices for remote vital signs monitoring. An accurate signal and a high diagnostic yield are critical for the cost-effectiveness of wearable health care monitoring systems and their widespread application in resource-constrained environments. Despite technological advances, the information acquired by these devices can be contaminated by motion artifacts (MA) leading to misdiagnosis or repeated procedures with increases in associated costs. This makes it necessary to develop methods to improve the quality of the signal acquired by these devices., Objective: We aimed to present a novel method for electrocardiogram (ECG) signal denoising to reduce MA. We aimed to analyze the method's performance and to compare its performance to that of existing approaches., Methods: We present the novel Redundant denoising Independent Component Analysis method for ECG signal denoising based on the redundant and simultaneous acquisition of ECG signals and movement information, multichannel processing, and performance assessment considering the information contained in the signal waveform. The method is based on data including ECG signals from the patient's chest and back, the acquisition of triaxial movement signals from inertial measurement units, a reference signal synthesized from an autoregressive model, and the separation of interest and noise sources through multichannel independent component analysis., Results: The proposed method significantly reduced MA, showing better performance and introducing a smaller distortion in the interest signal compared with other methods. Finally, the performance of the proposed method was compared to that of wavelet shrinkage and wavelet independent component analysis through the assessment of signal-to-noise ratio, dynamic time warping, and a proposed index based on the signal waveform evaluation with an ensemble average ECG., Conclusions: Our novel ECG denoising method is a contribution to converting wearable devices into medical monitoring tools that can be used to support the remote diagnosis and monitoring of cardiovascular diseases. A more accurate signal substantially improves the diagnostic yield of wearable devices. A better yield improves the devices' cost-effectiveness and contributes to their widespread application., (©Fabian Andres Castaño Usuga, Christian Gissel, Alher Mauricio Hernández. Originally published in JMIR Medical Informatics (https://medinform.jmir.org), 25.11.2022.)

Objective: This single-blind randomized controlled crossover pilot trial investigated whether hard or soft knee orthotics affect the back in action (BIA) test battery performance., Methods: Twenty-four healthy participants (13 males, 11 females) were randomly assigned into three equal groups differentiated through the order of device use. The data were collected in a laboratory setting. BIA test battery (balance tests, vertical jumps, and parkour hop tests) was run with a rigid orthotic device, a soft brace, or no aid in a crossover order. Analysis of Variance repeated measures and Friedman Test were used to calculate depended-group differences., Results: No significant or clinically relevant effect or differences was observed between running the BIA with a soft brace, rigid orthosis, or no aid ( p = 0.53-0.97) for all included tests. No adverse events have been observed., Conclusion: Soft and rigid knee braces do not affect performance in healthy participants. Missing experience with the devices might explain a few influences on feedback mechanisms. There is no disadvantage to be expected regarding healthy participants running back to sports.

Background: Contactless vital signs (VS) measurement with video photoplethysmography (vPPG), motion analysis (MA), and passive infrared thermometry (pIR) has shown promise., Objectives: To compare conventional (contact-based) and experimental contactless VS measurement approaches for emergency department (ED) walk-in triage in pandemic conditions., Methods: Patients' heart rates (HR), respiratory rates (RR), and temperatures were measured with cardiorespiratory monitor and vPPG, manual count and MA, and contact thermometers and pIR, respectively., Results: There were 475 walk-in ED patients studied (95% of eligible). Subjects were 35.2 ± 20.8 years old (range 4 days‒95 years); 52% female, 0.2% transgender; had Fitzpatrick skin type of 2.3 ± 1.4 (range 1‒6), Emergency Severity Index of 3.0 ± 0.6 (range 2‒5), and contact temperature of 36.83°C (range 35.89-39.4°C) (98.3°F [96.6‒103°F]). Pediatric HR and RR data were excluded from analysis due to research challenges associated with pandemic workflow. For a 30-s, unprimed "Triage" window in 377 adult patients, vPPG-MA acquired 377 (100%) HR measurements featuring a mean difference with cardiorespiratory monitor HR of 5.9 ± 12.8 beats/min (R = 0.6833) and 252 (66.8%) RR measurements featuring a mean difference with manual RR of -0.4 ± 2.6 beats/min (R = 0.8128). Subjects' Emergency Severity Index components based on conventional VS and contactless VS matched for 83.8% (HR) and 89.3% (RR). Filtering out vPPG-MA measurements with low algorithmic confidence reduced VS acquired while improving correlation with conventional measurements. The mean difference between contact and pIR temperatures was 0.83 ± 0.67°C (range -1.16-3.5°C) (1.5 ± 1.2°F [range -2.1-6.3°F]); pIR fever detection improved with post hoc adjustment for mean bias., Conclusion: Contactless VS acquisition demonstrated good agreement with contact methods during adult walk-in ED patient triage in pandemic conditions; clinical applications will need further study., (Copyright © 2022 Elsevier Inc. All rights reserved.)

The Athletic Shoulder (ASH) test was introduced as a tool for quantifying the ability to produce and transfer force across the shoulder girdle. Whether using the portable isometric-based strength training device Active5™ is a reliable alternative to a gold standard force plate for ASH testing purposes remains unknown; therefore, the present study determined the reliability and validity of Active5™ usage in the ASH test compared to force plates. Fifty-one healthy participants performed the ASH test using Active5™ and K-Force plates in three separate sessions. The maximal force was measured bilaterally in a prone position at three shoulder abduction angles, precisely at 180°, 135°, and 90°. The first rater carried out the first and third sessions, spaced at a one-week interval. A second rater performed the second session. The reliability was assessed using the intraclass correlation coefficient (ICC). The linear Pearson's correlation coefficient ( r ) calculation was used to determine the relationship between ASH test results using the two devices. The ICC = 0.77-0.99 result indicated good to excellent reliability for Active5™ usage. A high to a very high correlation between the two devices at 180° and 90° was noted ( r = 0.75-0.95). This data supports the isometric-based strength training device Active5™ as a reliable and valid tool for ASH test performance.

Parkinson's disease (PD) is the second most common progressive neurodegenerative disorder, affecting 6.2 million patients and causing disability and decreased quality of life. The research is oriented nowadays toward artificial intelligence (AI)-based wearables for early diagnosis and long-term PD monitoring. Our primary objective is the monitoring and assessment of gait in PD patients. We propose a wearable physiograph for qualitative and quantitative gait assessment, which performs bilateral tracking of the foot biomechanics and unilateral tracking of arm balance. Gait patterns are assessed by means of correlation. The surface plot of a correlation coefficient matrix, generated from the recorded signals, is classified using convolutional neural networks into physiological or PD-specific gait. The novelty is given by the proposed AI-based decisional support procedure for gait assessment. A proof of concept of the proposed physiograph is validated in a clinical environment on five patients and five healthy controls, proving to be a feasible solution for ubiquitous gait monitoring and assessment in PD. PD management demonstrates the complexity of the human body. A platform empowering multidisciplinary, AI-evidence-based decision support assessments for optimal dosing between drug and non-drug therapy could lay the foundation for affordable precision medicine.

Monitoring and treatment of severely ill COVID-19 patients in the ICU poses many challenges. The effort to understand the pathophysiology and progress of the disease requires high-quality annotated multi-parameter databases. We present CoCross, a platform that enables the monitoring and fusion of clinical information from in-ICU COVID-19 patients into an annotated database. CoCross consists of three components: (1) The CoCross4Pros native android application, a modular application, managing the interaction with portable medical devices, (2) the cloud-based data management services built-upon HL7 FHIR and ontologies, (3) the web-based application for intensivists, providing real-time review and analytics of the acquired measurements and auscultations. The platform has been successfully deployed since June 2020 in two ICUs in Greece resulting in a dynamic unified annotated database integrating clinical information with chest sounds and diagnostic imaging. Until today multisource data from 176 ICU patients were acquired and imported in the CoCross database, corresponding to a five-day average monitoring period including a dataset with 3477 distinct auscultations. The platform is well accepted and positively rated by the users regarding the overall experience.

Heart disease is the leading cause of death for men and women globally. The residual network (ResNet) evolution of electrocardiogram (ECG) technology has contributed to our understanding of cardiac physiology. We propose an artificial intelligence-enabled ECG algorithm based on an improved ResNet for a wearable ECG. The system hardware consists of a wearable ECG with conductive fabric electrodes, a wireless ECG acquisition module, a mobile terminal App, and a cloud diagnostic platform. The algorithm adopted in this study is based on an improved ResNet for the rapid classification of different types of arrhythmia. First, we visualize ECG data and convert one-dimensional ECG signals into two-dimensional images using Gramian angular fields. Then, we improve the ResNet-50 network model, add multistage shortcut branches to the network, and optimize the residual block. The ReLu activation function is replaced by a scaled exponential linear units (SELUs) activation function to improve the expression ability of the model. Finally, the images are input into the improved ResNet network for classification. The average recognition rate of this classification algorithm against seven types of arrhythmia signals (atrial fibrillation, atrial premature beat, ventricular premature beat, normal beat, ventricular tachycardia, atrial tachycardia, and sinus bradycardia) is 98.3%.

Conventional respiration measurement requires a separate device and/or can cause discomfort, so it is difficult to perform routinely, even for patients with respiratory diseases. The development of contactless respiration measurement technology would reduce discomfort and help detect and prevent fatal diseases. Therefore, we propose a respiration measurement method using a learning-based region-of-interest detector and a clustering-based respiration pixel estimation technique. The proposed method consists of a model for classifying whether a pixel conveys respiration information based on its variance and a method for classifying pixels with clear breathing components using the symmetry of the respiration signals. The proposed method was evaluated with the data of 14 men and women acquired in an actual environment, and it was confirmed that the average error was within approximately 0.1 bpm. In addition, a Bland-Altman analysis confirmed that the measurement result had no error bias, and regression analysis confirmed that the correlation of the results with the reference is high. The proposed method, designed to be inexpensive, fast, and robust to noise, is potentially suitable for practical use in clinical scenarios.

Intra-abdominal pressure (IAP) is closely correlated with intra-abdominal hypertension (IAH) and abdominal compartment syndrome (ACS) diagnoses, indicating the need for continuous monitoring. Early intervention for IAH and ACS has been proven to reduce the rate of morbidity. However, the current IAP monitoring method is a tedious process with a long calibration time for a single time point measurement. Thus, there is the need for an efficient and continuous way of measuring IAP. Herein, a stretchable capacitive pressure sensor with controlled microstructures embedded into a cylindrical elastomeric mold, fabricated as a pressure sensing sleeve, is presented. The sensing sleeve can be readily deployed onto intrabody catheter balloons for pressure measurement at the site. The thin and highly conformable nature of the pressure sensing sleeve captures the pressure change without hindering the functionality of the foley catheter balloon.

Previously, studies reported that falls analysis is possible in the elderly, when using wearable sensors. However, these devices cannot be worn daily, as they need to be removed and recharged from time-to-time due to their energy consumption, data transfer, attachment to the body, etc. This study proposes to introduce a radar sensor, an unobtrusive technology, for risk of falling analysis and combine its performance with an instrumented insole. We evaluated our methods on datasets acquired during a Timed Up and Go (TUG) test where a stride length (SL) was computed by the insole using three approaches. Only the SL from the third approach was not statistically significant ( p = 0.2083 > 0.05) compared to the one provided by the radar, revealing the importance of a sensor location on human body. While reducing the number of force sensors (FSR), the risk scores using an insole containing three FSRs and y-axis of acceleration were not significantly different ( p > 0.05) compared to the combination of a single radar and two FSRs. We concluded that contactless TUG testing is feasible, and by supplementing the instrumented insole to the radar, more precise information could be available for the professionals to make accurate decision., Competing Interests: The authors declare no conflict of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript, or in the decision to publish the results.

Remote monitoring of vital signs for studying sleep is a user-friendly alternative to monitoring with sensors attached to the skin. For instance, remote monitoring can allow unconstrained movement during sleep, whereas detectors requiring a physical contact may detach and interrupt the measurement and affect sleep itself. This study evaluates the performance of a cost-effective frequency modulated continuous wave (FMCW) radar in remote monitoring of heart rate and respiration in scenarios resembling a set of normal and abnormal physiological conditions during sleep. We evaluate the vital signs of ten subjects in different lying positions during various tasks. Specifically, we aim for a broad range of both heart and respiration rates to replicate various real-life scenarios and to test the robustness of the selected vital sign extraction methods consisting of fast Fourier transform based cepstral and autocorrelation analyses. As compared to the reference signals obtained using Embla titanium, a certified medical device, we achieved an overall relative mean absolute error of 3.6% (86% correlation) and 9.1% (91% correlation) for the heart rate and respiration rate, respectively. Our results promote radar-based clinical monitoring by showing that the proposed radar technology and signal processing methods accurately capture even such alarming vital signs as minimal respiration. Furthermore, we show that common parameters for heart rate variability can also be accurately extracted from the radar signal, enabling further sleep analyses.

The Sit-to-Stand (STS) is a widely used test of physical function to screen older people at risk of falls and frailty and is also one of the most important components of standard screening for sarcopenia. There have been many recent studies in which instrumented versions of the STS (iSTS) have been developed to provide additional parameters that could improve the accuracy of the STS test. This systematic review aimed to identify whether an iSTS is a viable alternative to a standard STS to identify older people at risk of falling, frailty, and sarcopenia. A total of 856 articles were found using the search strategy developed, with 12 articles retained in the review after screening based on the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. Six studies evaluated the iSTS in fallers, five studies in frailty and only one study in both fallers and frailty. The results showed that power and velocity parameters extracted from an iSTS have the potential to improve the accuracy of screening when compared to a standard STS. Future work should focus on standardizing the segmentation of the STS into phases to enable comparison between studies and to develop devices integrated into the chair used for the test to improve usability.

The current pandemic associated with the novel coronavirus (COVID-19) presents a new area of research with its own set of challenges. Creating unobtrusive remote monitoring tools for medical professionals that may aid in diagnosis, monitoring and contact tracing could lead to more efficient and accurate treatments, especially in this time of physical distancing. Audio based sensing methods can address this by measuring the frequency, severity and characteristics of the COVID-19 cough. However, the feasibility of accumulating coughs directly from patients is low in the short term. This article introduces a novel database (NoCoCoDa), which contains COVID-19 cough events obtained through public media interviews with COVID-19 patients, as an interim solution. After manual segmentation of the interviews, a total of 73 individual cough events were extracted and cough phase annotation was performed. Furthermore, the COVID-19 cough is typically dry but can present as a more productive cough in severe cases. Therefore, an investigation of cough sub-type (productive vs. dry) of the NoCoCoDa was performed using methods previously published by our research group. Most of the NoCoCoDa cough events were recorded either during or after a severe period of the disease, which is supported by the fact that 77% of the COVID-19 coughs were classified as productive based on our previous work. The NoCoCoDa is designed to be used for rapid exploration and algorithm development, which can then be applied to more extensive datasets and potentially real time applications. The NoCoCoDa is available for free to the research community upon request., (This work is licensed under a Creative Commons Attribution 4.0 License. For more information, see https://creativecommons.org/licenses/by/4.0/.)

With the development of flexible electronic materials, as well as the wide development and application of smartphones, the cloud, and wireless systems, flexible wearable sensor technology has a significant and far-reaching impact on the realization of personalized medical care and the reform of the consumer market in the future. However, due to the high requirements for accuracy, reliability, low power consumption, and less data error, the development of these potential areas is full of challenges. In order to solve these problems, this review mainly searches the literature from 2008 to May 2020, based on the PRISMA process. Based on them, this paper reviews the latest research progress of new flexible materials and different types of sensors for monitoring vital signs (including electrophysiological signals, body temperature, and respiratory frequency) in recent years. These materials and sensors can help realize accurate signal detection based on comfortable and sustainable observation, and may likely be applied to future daily clothing.

Background and Objective: Outpatient vital signs monitoring has a key role in medical diagnosis and treatment. However, ambulatory vital signs monitoring has great challenges to overcome, being the most important, the reduction of noise and Motion Artifacts, which hide essential information, particularly in Electrocardiographic signals. Despite efforts being made to reduce these artifacts, a comparative performance assessment of proposed techniques does not exist to the best of our knowledge and there are no enhancement level measurements obtained by the signals in the artifacts reduction. This article presents a new method based on Ensemble Average for the performance comparison of reported techniques for the processing and reduction of noise and artifacts in Electrocardiographic signals., Methods: The comparison was done using a dataset composed by six synthetic noised Electrocardiographic signals and six real one acquired from healthy volunteers that intentionally introduced Motion Artifacts. Several techniques that have reported positive results in the enhancement of Electrocardiographic signals were applied to this dataset to compare their performance in the reduction of Motion Artifacts. The Signal-to-Noise Ratio and the Ensemble Average as a distortion measurement were used to compare the performance of algorithms to produce an enhanced signal., Results: In agreement to previous reports, all studied methods show a significant improvement of the Signal-to-Noise Ratio. Concerning the distortion of the waveform, although all methods caused high distortion on the enhanced signal waveform, the Wavelet-ICA method showed the best performance. The percentage of signal distortion introduced by denoising techniques was evaluated through the proposed Ensemble Average Electrocardiographic method., Conclusions: It was found that the proposed method based on Ensemble Average offers a complementary way to measure the performance of denoising techniques when considering the introduced distortion in the waveform segments once the artifact reduction process was applied and not only the change in the Signal-to-Noise Ratio., (Copyright © 2019. Published by Elsevier B.V.)

Non-acid reflux is common in premature neonates. Current methods of diagnosing gastroesophageal reflux (GER) such as pH probes, multichannel impedance monitoring, X-rays, or endoscopy are either invasive or unable to diagnose non-acid reflux. Passage of a naso-esophageal tube is uncomfortable. Imaging studies are of short duration and may miss reflux entirely. Herein, we present proof of concept of a noninvasive accelerometric device that detects acid and non-acid reflux in premature infants. An accelerometer was taped over the subxiphoid process in patients suspected of having GER who were already scheduled for pH probe or multichannel impedance monitoring. The largest cohort was preterm infants, but term infants and toddlers were also studied. Low-frequency subaudible signals were obtained on a digital recorder (sampling rate 200 Hz) signals. Fast Fourier transforms graphically displayed the frequency and amplitude of signals. Data were then resampled at a rate of 60 Hz to create a spectrogram with a focused range of 0-30 Hz representing reflux-associated events. Proof of concept was attained through successful comparison with results from concurrent pH probes, multichannel impedance recordings, and ultrasound studies. We have thus validated accelerometry as a noninvasive method for assessing both acid and non-acid GER. The noninvasiveness of this diagnostic modality allows for repeated testing to assess the efficacy of anti-reflux medications, even when patients remain on antacids. This technology allows for more rational management of patients with GER and represents a major advance in the diagnosis and treatment of GER., (Copyright © 2019 by ASME.)

We report on the adaptation of a smartphone's rear-facing camera to function as a spectrometer that measures the spectrum of light scattered by common paper-based assay test strips. We utilize a cartridge that enables a linear series of test pads in a single strip to be swiped past the read head of the instrument while the phone's camera records video. The strip is housed in a custom-fabricated cartridge that slides through the instrument to facilitate illumination with white light from the smartphone's flash LED that is directed through an optical fiber. We demonstrate the ability to detect subtle changes in the scattered spectrum that enables quantitative analysis of single-analyte and multi-analyte strips. The demonstrated capability can be applied to broad classes of paper-based assays in which visual observation of colored strips is not sufficiently quantitative, and for which analysis of red-green-blue pixel values of a camera image are not capable of measuring complex scattered spectra.

Background: Avoidance to look others in the eye is a characteristic symptom of Autism Spectrum Disorders (ASD), and it has been hypothesised that quantitative monitoring of gaze patterns could be useful to objectively evaluate treatments. However, tools to measure gaze behaviour on a regular basis at a manageable cost are missing. In this paper, we investigated whether a smartphone-based tool could address this problem. Specifically, we assessed the accuracy with which the phone-based, state-of-the-art eye-tracking algorithm iTracker can distinguish between gaze towards the eyes and the mouth of a face displayed on the smartphone screen. This might allow mobile, longitudinal monitoring of gaze aversion behaviour in ASD patients in the future., Results: We simulated a smartphone application in which subjects were shown an image on the screen and their gaze was analysed using iTracker. We evaluated the accuracy of our set-up across three tasks in a cohort of 17 healthy volunteers. In the first two tasks, subjects were shown different-sized images of a face and asked to alternate their gaze focus between the eyes and the mouth. In the last task, participants were asked to trace out a circle on the screen with their eyes. We confirm that iTracker can recapitulate the true gaze patterns, and capture relative position of gaze correctly, even on a different phone system to what it was trained on. Subject-specific bias can be corrected using an error model informed from the calibration data. We compare two calibration methods and observe that a linear model performs better than a previously proposed support vector regression-based method., Conclusions: Under controlled conditions it is possible to reliably distinguish between gaze towards the eyes and the mouth with a smartphone-based set-up. However, future research will be required to improve the robustness of the system to roll angle of the phone and distance between the user and the screen to allow deployment in a home setting. We conclude that a smartphone-based gaze-monitoring tool provides promising opportunities for more quantitative monitoring of ASD.

Sensing devices with wearability would open the door to many advanced applications including soft robotics, artificial intelligence, and healthcare monitoring. Here, inspired by the configuration of the human epidermis, we present a flexible three-dimensional (3D) cellular sensor array (CSA) via a one-step thermally induced phase separation method. The CSA was framed by the 3D cellular electret with caged piezoelectric nanoparticles, which was ultrathin (80 μm), lightweight, and highly robust. For biomedical sensing, the 3D-CSA holds a decent pressure sensitivity up to 0.19 V kPa -1 with a response time of less than 16 ms. Owing to its rigid structural symmetry, the 3D-CSA could be identically operated from its both sides. It was demonstrated to successfully measure the human heartbeat, detect the eyeball motion for sleeping monitoring, and tactile imaging. Mimicking the functionalities of the human skin with a self-powered operation feature, the 3D-CSA was expected to represent a substantial advancement in wearable electronics for healthcare.

Background: Remote photoplethysmography (rPPG) is a promising optical method for non-contact assessment of pulse rate (PR) from video recordings. In order to implement the method in real-time applications, it is necessary for the rPPG algorithms to be capable of eliminating as many distortions from the pulse signal as possible., Methods: In order to increase the degrees-of-freedom of the distortion elimination, the dimensionality of the RGB video signals is increased by the wavelet transform decomposition using the generalized Morse wavelet. The proposed Continuous-Wavelet-Transform-based Sub-Band rPPG method (SB-CWT) is evaluated on the 101 publicly available RGB facial video recordings and corresponding reference blood volume pulse (BVP) signals taken from the MMSE-HR database. The performance of the SB-CWT is compared with the performance of the state-of-the-art Sub-band rPPG (SB)., Results: Median signal-to-noise ratio (SNR) for the proposed SB-CWT ranges from 6.63 to 10.39 dB and for the SB from 4.23 to 6.24 dB. The agreement between the estimated PRs from rPPG pulse signals and the reference signals in terms of the coefficients of determination ranges from 0.81 to 0.91 for SB-CWT and from 0.41 to 0.47 for SB. All the correlation coefficients are statistically significant ( p < 0.001). The Bland-Altman plots show that mean difference range from 5.37 to 1.82 BPM for SB-CWT and from 22.18 to 18.80 BPM for SB., Discussion: The results show that the proposed SB-CWT outperforms SB in terms of SNR and the agreement between the estimated PRs from RGB video signals and PRs from the reference BVP signals., Competing Interests: The authors declare that they have no competing interests.

Objective: single-camera-based gait monitoring is unobtrusive, inexpensive, and easy-to-use to monitor daily gait of seniors in their homes. However, most studies require subjects to walk perpendicularly to camera's optical axis or along some specified routes, which limits its application in elderly home monitoring. To build unconstrained monitoring environments, we propose a method to measure step length symmetry ratio (a useful gait parameter representing gait symmetry without significant relationship with age) from unconstrained straight walking using a single camera, without strict restrictions on walking directions or routes., Methods: according to projective geometry theory, we first develop a calculation formula of step length ratio for the case of unconstrained straight-line walking. Then, to adapt to general cases, we propose to modify noncollinear footprints, and accordingly provide general procedure for step length ratio extraction from unconstrained straight walking., Results: Our method achieves a mean absolute percentage error (MAPE) of 1.9547% for 15 subjects' normal and abnormal side-view gaits, and also obtains satisfactory MAPEs for non-side-view gaits (2.4026% for 45°-view gaits and 3.9721% for 30°-view gaits). The performance is much better than a well-established monocular gait measurement system suitable only for side-view gaits with a MAPE of 3.5538%., Conclusion: Independently of walking directions, our method can accurately estimate step length ratios from unconstrained straight walking., Significance: This demonstrates our method is applicable for elders' daily gait monitoring to provide valuable information for elderly health care, such as abnormal gait recognition, fall risk assessment, etc., Objective: single-camera-based gait monitoring is unobtrusive, inexpensive, and easy-to-use to monitor daily gait of seniors in their homes. However, most studies require subjects to walk perpendicularly to camera's optical axis or along some specified routes, which limits its application in elderly home monitoring. To build unconstrained monitoring environments, we propose a method to measure step length symmetry ratio (a useful gait parameter representing gait symmetry without significant relationship with age) from unconstrained straight walking using a single camera, without strict restrictions on walking directions or routes., Methods: according to projective geometry theory, we first develop a calculation formula of step length ratio for the case of unconstrained straight-line walking. Then, to adapt to general cases, we propose to modify noncollinear footprints, and accordingly provide general procedure for step length ratio extraction from unconstrained straight walking., Results: Our method achieves a mean absolute percentage error (MAPE) of 1.9547% for 15 subjects' normal and abnormal side-view gaits, and also obtains satisfactory MAPEs for non-side-view gaits (2.4026% for 45°-view gaits and 3.9721% for 30°-view gaits). The performance is much better than a well-established monocular gait measurement system suitable only for side-view gaits with a MAPE of 3.5538%., Conclusion: Independently of walking directions, our method can accurately estimate step length ratios from unconstrained straight walking., Significance: This demonstrates our method is applicable for elders' daily gait monitoring to provide valuable information for elderly health care, such as abnormal gait recognition, fall risk assessment, etc.

An aging and more sedentary population requires interventions aimed at monitoring physical activity, particularly within the home. This research uses simulation, optimization, and regression analyses to assess the feasibility of using a small number of sensors to track movement and infer physical activity levels of older adults. Based on activity data from the American Time Use Survey and assisted living apartment layouts, we determined that using three to four doorway sensors can be used to effectively capture a sufficient amount of movements in order to estimate activity. The research also identified preferred approaches for assigning sensor locations, evaluated the error magnitude inherent in the approach, and developed a methodology to identify which apartment layouts would be best suited for these technologies.

Operation time of implantable electronic devices is largely constrained by the lifetime of batteries, which have to be replaced periodically by surgical procedures once exhausted, causing physical and mental suffering to patients and increasing healthcare costs. Besides the efficient scavenging of the mechanical energy of internal organs, this study proposes a self-powered, flexible, and one-stop implantable triboelectric active sensor (iTEAS) that can provide continuous monitoring of multiple physiological and pathological signs. As demonstrated in human-scale animals, the device can monitor heart rates, reaching an accuracy of ∼99%. Cardiac arrhythmias such as atrial fibrillation and ventricular premature contraction can be detected in real-time. Furthermore, a novel method of monitoring respiratory rates and phases is established by analyzing variations of the output peaks of the iTEAS. Blood pressure can be independently estimated and the velocity of blood flow calculated with the aid of a separate arterial pressure catheter. With the core-shell packaging strategy, monitoring functionality remains excellent during 72 h after closure of the chest. The in vivo biocompatibility of the device is examined after 2 weeks of implantation, proving suitability for practical use. As a multifunctional biomedical monitor that is exempt from needing an external power supply, the proposed iTEAS holds great potential in the future of the healthcare industry.

Adolescent idiopathic scoliosis is a spinal deformity affecting 2-3% of adolescents. Brace treatment, the most common non-surgical treatment, uses a hard plastic orthotic shell to prevent progression of the deformity. Previous studies have found association between treatment outcome and patients' compliance with the prescribed brace-wear regimen. However, the exact relationship between compliance and treatment outcome has yet to be elucidated. Current compliance monitoring techniques may not be providing enough information about patients' brace-wear habits. Building on previous work, we present a new compliance monitor which records both temperature and force applied to the patient's body. The combination of temperature and force readings shows both how often and how tightly the brace is worn. The new monitor is designed for minimal size and power consumption, measuring 5.2 cm × 2.5 cm × 0.8 cm, with a battery life of approximately one year. Seven patients wore the monitor in this pilot study. The temperature-based compliance estimate differed significantly from the force-based estimate in four out of seven cases. This suggests that some patients may wear their braces very loosely, and that existing temperature-only or force-only compliance monitors may not be giving a complete picture of brace-wear habits., (Copyright © 2015 IPEM. Published by Elsevier Ltd. All rights reserved.)

We demonstrate the feasibility of using optical coherence tomography (OCT) to image and detect 2.8 μ m diameter microparticles (stationary and moving) on a highly-reflective gold surface both in clear media and under skin in vitro . The OCT intensity signal can clearly report the microparticle count, and the OCT response to the number of microparticles shows a good linearity. The detect ability of the intensity change (2.9% ± 0.5%) caused by an individual microparticle shows the high sensitivity of monitoring multiple particles using OCT. An optical sensing method based on this feasibility study is described for continuously measuring blood sugar levels in the subcutaneous tissue, and a molecular recognition unit is designed using competitive binding to modulate the number of bound microparticles as a function of glucose concentration. With further development, an ultra-small, implantable sensor might provide high specificity and sensitivity for long-term continuous monitoring of blood glucose concentration.

Intraoral devices for bite-force sensing have several applications in odontology and maxillofacial surgery, as bite-force measurements provide additional information to help understand the characteristics of bruxism disorders and can also be of help for the evaluation of post-surgical evolution and for comparison of alternative treatments. A new system for measuring human bite forces is proposed in this work. This system has future applications for the monitoring of bruxism events and as a complement for its conventional diagnosis. Bruxism is a pathology consisting of grinding or tight clenching of the upper and lower teeth, which leads to several problems such as lesions to the teeth, headaches, orofacial pain and important disorders of the temporomandibular joint. The prototype uses a magnetic field communication scheme similar to low-frequency radio frequency identification (RFID) technology (NFC). The reader generates a low-frequency magnetic field that is used as the information carrier and powers the sensor. The system is notable because it uses an intra-mouth passive sensor and an external interrogator, which remotely records and processes information regarding a patient's dental activity. This permits a quantitative assessment of bite-force, without requiring intra-mouth batteries, and can provide supplementary information to polysomnographic recordings, current most adequate early diagnostic method, so as to initiate corrective actions before irreversible dental wear appears. In addition to describing the system's operational principles and the manufacture of personalized prototypes, this report will also demonstrate the feasibility of the system and results from the first in vitro and in vivo trials.