Monitoring postures and motions of hospitalized patients using sensor technology: a scoping review.

BACKGROUND: Sensor technology could provide solutions to monitor postures and motions and to help hospital patients reach their rehabilitation goals with minimal supervision. Synthesized information on device applications and methodology is lacking. OBJECTIVES: The purpose of this scoping review was to provide an overview of device applications and methodological approaches to monitor postures and motions in hospitalized patients using sensor technology. METHODS: A systematic search of Embase, Medline, Web of Science and Google Scholar was completed in February 2023 and updated in March 2024. Included studies described populations of hospitalized adults with short admission periods and interventions that use sensor technology to objectively monitor postures and motions. Study selection was performed by two authors independently of each other. Data extraction and narrative analysis focused on the applications and methodological approaches of included articles using a personalized standard form to extract information on device, measurement and analysis characteristics of included studies and analyse frequencies and usage. RESULTS: A total of 15.032 articles were found and 49 articles met the inclusion criteria. Devices were most often applied in older adults (n = 14), patients awaiting or after surgery (n = 14), and stroke (n = 6). The main goals were gaining insight into patient physical behavioural patterns (n = 19) and investigating physical behaviour in relation to other parameters such as muscle strength or hospital length of stay (n = 18). The studies had heterogeneous study designs and lacked completeness in reporting on device settings, data analysis, and algorithms. Information on device settings, data analysis, and algorithms was poorly reported. CONCLUSIONS: Studies on monitoring postures and motions are heterogeneous in their population, applications and methodological approaches. More uniformity and transparency in methodology and study reporting would improve reproducibility, interpretation and generalization of results. Clear guidelines for reporting and the collection and sharing of raw data would benefit the field by enabling study comparison and reproduction.

In a clinical setting, wearables are currently used to monitor postures and motions in a wide variety of study applications and hospital populations.Measurement of postures and motions in the hospital setting is characterized by methodological heterogeneity. This poses a significant challenge, impacting the interpretation of results and hindering meaningful comparisons between studiesFollowing guidelines for reporting and the collection and sharing of raw data would benefit the field.

A personalized clinical assessment: multi-sensor approach for understanding musculoskeletal health in the frail population.

BACKGROUND: Sarcopenia is a muscle disorder causing a progressive reduction of muscle mass and strength, but the mechanism of its manifestation is still partially unknown. The three main parameters to assess are: muscle strength, muscle volume or quality and low physical performance. There is not a definitive approach to assess the musculoskeletal condition of frail population and often the available tests to be performed in those clinical bedridden patients is reduced because of physical impairments. In this paper, we propose a novel instrumental multi-domain and non-invasive approach during a well-defined protocol of measurements for overcoming these limitations. A group of 28 bedridden elder people, subjected to surgery after hip fracture, was asked to perform voluntary isometric contractions at the 80% of their maximum voluntary contraction with the non-injured leg. The sensor employed before and/or during the exercise were: ultrasound to determine the muscle architecture (vastus lateralis); force acquisition with a load cell placed on the chair, giving an indication of the muscle strength; surface electromyography (EMG) for monitoring muscular electrical activity; time-domain (TD) near-infrared spectroscopy (NIRS) for evaluating muscle oxidative metabolism. RESULTS: A personalized "report card" for each subject was created. It includes: the force diagram (both instantaneous and cumulative, expected and measured); the EMG-force diagram for a comparison between EMG derived median frequency and measured force; two graphs related to the hemodynamic parameters for muscle oxidative metabolism evaluation, i.e., oxy-, deoxy-, total-hemoglobin and tissue oxygen saturation for the whole exercise period. A table with the absolute values of the previous hemodynamic parameters during the rest and the ultrasound related parameters are also included. CONCLUSIONS: In this work, we present the union of protocols, multi-domain sensors and parameters for the evaluation of the musculoskeletal condition. The novelties are the use of sensors of different nature, i.e., force, electrical and optical, together with a new way to visualize and combine the results, by means of a concise, exhaustive and personalized medical report card for each patient. This assessment, totally non-invasive, is focused on a bedridden population, but can be extended to the monitoring of rehabilitation progresses or of the training of athletes.

Application of noncontact sensors for cardiopulmonary physiology and body weight monitoring at home: A narrative review.

Monitoring health status at home has garnered increasing interest. Therefore, this study investigated the potential feasibility of using noncontact sensors in actual home settings. We searched PubMed for relevant studies published until February 19, 2024, using the keywords "home-based," "home," "monitoring," "sensor," and "noncontact." The studies included in this review involved the installation of noncontact sensors in actual home settings and the evaluation of their performance for health status monitoring. Among the 3 included studies, 2 monitored respiratory status during sleep and 1 monitored body weight and cardiopulmonary physiology. Measurements such as heart rate, respiratory rate, and body weight obtained with noncontact sensors were compared with the results obtained from polysomnography, polygraphy, and commercial scales. All included studies demonstrated that noncontact sensors produced results comparable to those of standard measurement tools, confirming their excellent capability for biometric measurements. Overall, noncontact sensors have sufficient potential for monitoring health status at home.

Agreement of cardiac index measurements between ultrasonic cardiac output monitor and transthoracic echocardiography in neonates.

OBJECTIVES: To evaluate the agreement of cardiac index (CI) calculated by Ultrasonic sonic cardiac output monitor (USCOM) and transthoracic thoracic echocardiography (TTE) in order to know if we can recommend USCOM in our pediatric intensive care unit (PICU). DESIGN: Prospective observational evaluative study carried out over a period of 3 months Setting: PICU at children's hospital in Tunis Participants: All newborns without tracheostomy or a known congenital heart disease, admitted to the PICU during the study period were enrolled. INTERVENTIONS: Paired and consecutive measurements of CI were obtained in all patients with both technologies. All measurements by TTE and USCOM were performed by two distinct operators. It is the average of three successive measures of the CI, in the same patient, with each technology, which was considered. Agreement of CI between the 2 techniques was assessed by Bland-Altman analysis and percentage error. MEASUREMENTS AND MAIN RESULTS: Forty-two infants were analyzed with the mean (standard deviation) gestation 36 weeks ( 5 days), age 1 days (1.09) , and weight 2.9 kg (0.87). Respiratory failure was the main cause of admission 75%. At the time of the study, 33 (75.%) patients were ventilated artificially. Bias (mean difference) of the CI between the two methods was 1.2 l/min/m2 and precision (± 2 SD of differences) was 1.08 l/min/m2. The MPE of CI measurement for USCOM vs TTE was 54.9%. CONCLUSIONS: The USCOM showed a poor agreement to TTE measures of CI. The two methods cannot be considered interchangeable.

Flexible Microfluidic Strain Sensor Made with Poly(3,4-ethylenedioxythiophene):polystyrenesulfonate-MXene-Au Nanocomposites for Monitoring Physiological Signals.

Flexible strain sensors have been widely used in wearable electronics. However, the fabrication of flexible strain sensors with a large strain detection range, high sensitivity, and negligible hysteresis remains a formidable challenge, even after enormous advancements in the field. Herein, a flexible microfluidic strain sensor was fabricated by filling poly(3,4-ethylenedioxythiophene):polystyrenesulfonate-MXene-gold (PEDOT:PSS-MXene-Au) nanocomposites into microchannels in an elastic matrix. Owing to the unique properties of the nanofiller and Ecoflex elastomer microchannel, the microfluidic strain sensor detected a strain of 0%-500% with low hysteresis (2.4%), high sensitivity (guage factor = 25.4), short response times (∼86 ms), and good durability. Moreover, the flexible microfluidic sensor was used to detect various physiological signals and human activities, control a mechanical hand, and capture hand motions in real time. As demonstrated by its good performance, the proposed flexible microfluidic sensor holds great potential in applications such as wearable electronics, physiological signal monitoring and human-machine interactions.

Artificial Intelligence-Driven Prognosis of Respiratory Mechanics: Forecasting Tissue Hysteresivity Using Long Short-Term Memory and Continuous Sensor Data.

Tissue hysteresivity is an important marker for determining the onset and progression of respiratory diseases, calculated from forced oscillation lung function test data. This study aims to reduce the number and duration of required measurements by combining multivariate data from various sensing devices. We propose using the Forced Oscillation Technique (FOT) lung function test in both a low-frequency prototype and the commercial RESMON device, combined with continuous monitoring from the Equivital (EQV) LifeMonitor and processed by artificial intelligence (AI) algorithms. While AI and deep learning have been employed in various aspects of respiratory system analysis, such as predicting lung tissue displacement and respiratory failure, the prediction or forecasting of tissue hysteresivity remains largely unexplored in the literature. In this work, the Long Short-Term Memory (LSTM) model is used in two ways: (1) to estimate the hysteresivity coefficient η using heart rate (HR) data collected continuously by the EQV sensor, and (2) to forecast η values by first predicting the heart rate from electrocardiogram (ECG) data. Our methodology involves a rigorous two-hour measurement protocol, with synchronized data collection from the EQV, FOT, and RESMON devices. Our results demonstrate that LSTM networks can accurately estimate the tissue hysteresivity parameter η, achieving an R2 of 0.851 and a mean squared error (MSE) of 0.296 for estimation, and forecast η with an R2 of 0.883 and an MSE of 0.528, while significantly reducing the number of required measurements by a factor of three (i.e., from ten to three) for the patient. We conclude that our novel approach minimizes patient effort by reducing the measurement time and the overall ambulatory time and costs while highlighting the potential of artificial intelligence methods in respiratory monitoring.

Design and Evaluation of a Novel Venturi-Based Spirometer for Home Respiratory Monitoring.

The high cost and limited availability of home spirometers pose a significant barrier to effective respiratory disease management and monitoring. To address this challenge, this paper introduces a novel Venturi-based spirometer designed for home use, leveraging the Bernoulli principle. The device features a 3D-printed Venturi tube that narrows to create a pressure differential, which is measured by a differential pressure sensor and converted into airflow rate. The airflow is then integrated over time to calculate parameters such as the Forced Vital Capacity (FVC) and Forced Expiratory Volume in one second (FEV1). The system also includes a bacterial filter for hygienic use and a circuit board for data acquisition and streaming. Evaluation with eight healthy individuals demonstrated excellent test-retest reliability, with intraclass correlation coefficients (ICCs) of 0.955 for FVC and 0.853 for FEV1. Furthermore, when compared to standard Pulmonary Function Test (PFT) equipment, the spirometer exhibited strong correlation, with Pearson correlation coefficients of 0.992 for FVC and 0.968 for FEV1, and high reliability, with ICCs of 0.987 for FVC and 0.907 for FEV1. These findings suggest that the Venturi-based spirometer could significantly enhance access to spirometry at home. However, further large-scale validation and reliability studies are necessary to confirm its efficacy and reliability for widespread use.

The Utility of Calibrating Wearable Sensors before Quantifying Infant Leg Movements.

While interest in using wearable sensors to measure infant leg movement is increasing, attention should be paid to the characteristics of the sensors. Specifically, offset error in the measurement of gravitational acceleration (g) is common among commercially available sensors. In this brief report, we demonstrate how we measured the offset and other errors in three different off-the-shelf wearable sensors available to professionals and how they affected a threshold-based movement detection algorithm for the quantification of infant leg movement. We describe how to calibrate and correct for these offsets and how conducting this improves the reproducibility of results across sensors.

Penetrating Barriers: Noncontact Measurement of Vital Bio Signs Using Radio Frequency Technology.

The noninvasive measurement and sensing of vital bio signs, such as respiration and cardiopulmonary parameters, has become an essential part of the evaluation of a patient's physiological condition. The demand for new technologies that facilitate remote and noninvasive techniques for such measurements continues to grow. While previous research has made strides in the continuous monitoring of vital bio signs using lasers, this paper introduces a novel technique for remote noncontact measurements based on radio frequencies. Unlike laser-based methods, this innovative approach offers the advantage of penetrating through walls and tissues, enabling the measurement of respiration and heart rate. Our method, diverging from traditional radar systems, introduces a unique sensing concept that enables the detection of micro-movements in all directions, including those parallel to the antenna surface. The main goal of this work is to present a novel, simple, and cost-effective measurement tool capable of indicating changes in a subject's condition. By leveraging the unique properties of radio frequencies, this technique allows for the noninvasive monitoring of vital bio signs without the need for physical contact or invasive procedures. Moreover, the ability to penetrate barriers such as walls and tissues opens new possibilities for remote monitoring in various settings, including home healthcare, hospital environments, and even search and rescue operations. In order to validate the effectiveness of this technique, a series of experiments were conducted using a prototype device. The results demonstrated the feasibility of accurately measuring respiration patterns and heart rate remotely, showcasing the potential for real-time monitoring of a patient's physiological parameters. Furthermore, the simplicity and low-cost nature of the proposed measurement tool make it accessible to a wide range of users, including healthcare professionals, caregivers, and individuals seeking to monitor their own health.

IoT-Based Wireless System for Gait Kinetics Monitoring in Multi-Device Therapeutic Interventions.

This study presents an IoT-based gait analysis system employing insole pressure sensors to assess gait kinetics. The system integrates piezoresistive sensors within a left foot insole, with data acquisition managed using an ESP32 board that communicates via Wi-Fi through an MQTT IoT framework. In this initial protocol study, we conducted a comparative analysis using the Zeno system, supported by PKMAS as the gold standard, to explore the correlation and agreement of data obtained from the insole system. Four volunteers (two males and two females, aged 24-28, without gait disorders) participated by walking along a 10 m Zeno system path, equipped with pressure sensors, while wearing the insole system. Vertical ground reaction force (vGRF) data were collected over four gait cycles. The preliminary results indicated a strong positive correlation (r = 0.87) between the insole and the reference system measurements. A Bland-Altman analysis further demonstrated a mean difference of approximately (0.011) between the two systems, suggesting a minimal yet significant bias. These findings suggest that piezoresistive sensors may offer a promising and cost-effective solution for gait disorder assessment and monitoring. However, operational factors such as high temperatures and sensor placement within the footwear can introduce noise or unwanted signal activation. The communication framework proved functional and reliable during this protocol, with plans for future expansion to multi-device applications. It is important to note that additional validation studies with larger sample sizes are required to confirm the system's reliability and robustness for clinical and research applications.

Towards the Instrumentation of Facemasks Used as Personal Protective Equipment for Unobtrusive Breathing Monitoring of Workers.

This study focuses on the integration and validation of a filtering face piece 3 (FFP3) facemask module for monitoring breathing activity in industrial environments. The key objective is to ensure accurate, real-time respiratory rate (RR) monitoring while maintaining workers' comfort. RR monitoring is conducted through temperature variations detected using temperature sensors tested in two configurations: sensor t1, integrated inside the exhalation valve and necessitating structural mask modifications, and sensor t2, mounted externally in a 3D-printed structure, thus preserving its certification as a piece of personal protective equipment (PPE). Ten healthy volunteers participated in static and dynamic tests, simulating typical daily life and industrial occupational activities while wearing the breathing activity monitoring module and a chest strap as a reference instrument. These tests were carried out in both indoor and outdoor settings. The results demonstrate comparable mean absolute error (MAE) for t1 and t2 in both indoor (i.e., 0.31 bpm and 0.34 bpm) and outdoor conditions (i.e., 0.43 bpm and 0.83 bpm). During simulated working activities, both sensors showed consistency with MAE values in static tests and were not influenced by motion artifacts, with more than 97% of RR estimated errors within ±2 bpm. These findings demonstrate the effectiveness of integrating a smart module into protective masks, enhancing occupational health monitoring by providing continuous and precise RR data without requiring additional wearable devices.

Implementing Autonomous Control in the Digital-Twins-Based Internet of Robotic Things for Remote Patient Monitoring.

Conventional patient monitoring methods require skin-to-skin contact, continuous observation, and long working shifts, causing physical and mental stress for medical professionals. Remote patient monitoring (RPM) assists healthcare workers in monitoring patients distantly using various wearable sensors, reducing stress and infection risk. RPM can be enabled by using the Digital Twins (DTs)-based Internet of Robotic Things (IoRT) that merges robotics with the Internet of Things (IoT) and creates a virtual twin (VT) that acquires sensor data from the physical twin (PT) during operation to reflect its behavior. However, manual navigation of PT causes cognitive fatigue for the operator, affecting trust dynamics, satisfaction, and task performance. Also, operating manual systems requires proper training and long-term experience. This research implements autonomous control in the DTs-based IoRT to remotely monitor patients with chronic or contagious diseases. This work extends our previous paper that required the user to manually operate the PT using its VT to collect patient data for medical inspection. The proposed decision-making algorithm enables the PT to autonomously navigate towards the patient's room, collect and transmit health data, and return to the base station while avoiding various obstacles. Rather than manually navigating, the medical personnel direct the PT to a specific target position using the Menu buttons. The medical staff can monitor the PT and the received sensor information in the pre-built virtual environment (VE). Based on the operator's preference, manual control of the PT is also achievable. The experimental outcomes and comparative analysis verify the efficiency of the proposed system.

Exploring Clinical Practices of Critical Alarm Settings in Intensive Care Units: A Retrospective Study of 60,000 Patient Stays from the MIMIC-IV Database.

In Intensive Care Unit (ICU), the settings of the critical alarms should be sensitive and patient-specific to detect signs of deteriorating health without ringing continuously, but alarm thresholds are not always calibrated to operate this way. An assessment of the connection between critical alarm threshold settings and the patient-specific variables in ICU would deepen our understanding of the issue. The aim of this retrospective descriptive and exploratory study was to assess this relationship using a large cohort of ICU patient stays. A retrospective study was conducted on some 70,000 ICU stays taken from the MIMIC-IV database. Critical alarm threshold values and threshold modification frequencies were examined. The link between these alarm threshold settings and 30 patient variables was then explored by computing the Shapley values of a Random Tree Forest model, fitted with patient variables and alarm settings. The study included 57,667 ICU patient stays. Alarm threshold values and alarm threshold modification frequencies exhibited the same trend: they were influenced by the vital sign monitored, but almost never by the patient's overall health status. This exploratory study also placed patients' vital signs as the most important variables, far ahead of medication. In conclusion, alarm settings were rigid and mechanical and were rarely adapted to the evolution of the patient. The management of alarms in ICU appears to be imperfect, and a different approach could result in better patient care and improved quality of life at work for staff.

Nanostructured NiS2-based flexible smart sensors for human respiration monitoring.

The growing demand for wearable healthcare devices has led to an urgent need for cost-effective, wireless and portable breath monitoring systems. However, it is essential to explore novel nanomaterials that combine state-of-the-art flexible sensors with high performance and sensing capabilities along with scalability and industrially acceptable processing. In this study, we demonstrate a highly efficient NiS2-based flexible capacitive sensor fabricated via a solution-processible route using a novel single-source precursor [Ni{S2P(OPr)2}2]. The developed sensor could precisely detect the human respiration rate and exhibit rapid responsiveness, exceptional sensitivity and selectivity at ambient temperatures, with an ultra-fast response and recovery. The device effectively differentiates the exhaled breath patterns including slow, fast, oral and nasal breath, as well as post-exercise breath rates. Moreover, the sensor shows outstanding bending stability, repeatability, reliable and robust sensing performance and is capable of contactless sensing. The sensor was further employed with a user-friendly wireless interface to facilitate smartphone-enabled real-time breath monitoring systems. This work opens up numerous avenues for cost-effective, sustainable and versatile sensors with potential applications for Internet of Things-based flexible and wearable electronics.This article is part of the theme issue 'Celebrating the 15th anniversary of the Royal Society Newton International Fellowship'.

High-Performance Stretchable Strain Sensors Based on Auxetic Fabrics for Human Motion Detection.

Wearable strain sensors play a pivotal role in real-time human motion detection and health monitoring. Traditional fabric-based strain sensors, typically with a positive Poisson's ratio, face challenges in maintaining sensitivity and comfort during human motion due to conflicting resistance changes in different strain directions. In this work, high-performance stretchable strain sensors are developed based on graphene-modified auxetic fabrics (GMAF) for human motion detection in smart wearable devices. The proposed GMAF sensors, with a negative Poisson's ratio achieved through commercially available warp-knitting technology, exhibit an 8-fold improvement in sensitivity compared to conventional plain fabric sensors. The unique auxetic fabric structure enhances sensitivity by synchronizing resistance changes in both wale and course directions. The GMAF sensors demonstrate excellent washability, showing only slight degradation in auxeticity and an acceptable increase in resistance after 10 standard wash cycles. The GMAF sensors maintain stability under different strain levels and various motion frequencies, emphasizing their dynamic performance. The sensors exhibit superior conformability to joint movements, which effectively monitor a full range of motions, including joint bending, sports activities, and subtle actions like coughing and swallowing. The research underscores a promising approach to achieve industrial-scale production of wearable sensors with improved performance and comfort through fabric structure design.

Designing a practical fatigue detection system: A review on recent developments and challenges.

INTRODUCTION: Fatigue is considered to have a life-threatening effect on human health and it has been an active field of research in different sectors. Deploying wearable physiological sensors helps to detect the level of fatigue objectively without any concern of bias in subjective assessment and interfering with work. METHODS: This paper provides an in-depth review of fatigue detection approaches using physiological signals to pinpoint their main achievements, identify research gaps, and recommend avenues for future research. The review results are presented under three headings, including: signal modality, experimental environments, and fatigue detection models. Fatigue detection studies are first divided based on signal modality into uni-modal and multi-modal approaches. Then, the experimental environments utilized for fatigue data collection are critically analyzed. At the end, the machine learning models used for the classification of fatigue state are reviewed. PRACTICAL APPLICATIONS: The directions for future research are provided based on critical analysis of past studies. Finally, the challenges of objective fatigue detection in the real-world scenario are discussed.

The Potential Use and Value of a Wearable Monitoring Bracelet for Patients With Chronic Obstructive Pulmonary Disease: Qualitative Study Investigating the Patient and Health Care Professional Perspectives.

BACKGROUND: The occurrence of exacerbations has major effects on the health of people with chronic obstructive pulmonary disease (COPD). Monitoring devices that measure (vital) parameters hold promise for timely identification and treatment of exacerbations. Stakeholders' perspectives on the use of monitoring devices are of importance for the successful development and implementation of a device. OBJECTIVE: This study aimed to explore the potential use and value of a wearable monitoring bracelet (MB) for patients with COPD at high risk for exacerbation. The perspectives of health care professionals as well as patients were examined, both immediately after hospitalization and over a longer period. Furthermore, potential facilitators and barriers to the use and implementation of an MB were explored. METHODS: Data for this qualitative study were collected from January to April 2023. A total of 11 participants (eg, n=6 health care professionals [HCPs], 2 patients, and 3 additional patients) participated. In total, 2 semistructured focus groups were conducted via video calls; 1 with HCPs of various professional backgrounds and 1 with patients. In addition, 3 semistructured individual interviews were held with patients. The interviews and focus groups addressed attitudes, wishes, needs, as well as factors that could either support or impede the potential MB use. Data from interviews and focus groups were coded and analyzed according to the principles of the framework method. RESULTS: HCPs and patients both predominantly emphasized the importance of an MB in terms of promptly identifying exacerbations by detecting deviations from normal (vital) parameters, and subsequently alerting users. According to HCPs, this is how an MB should support the self-management of patients. Most participants did not anticipate major differences in value and use of an MB between the short-term and the long-term periods after hospitalization. Facilitators of the potential use and implementation of an MB that participants highlighted were ease of use and some form of support for patients in using an MB and interpreting the data. HCPs as well as patients expressed concerns about potential costs as a barrier to use and implementation. Another barrier that HCPs mentioned, was the prerequisite of digital literacy for patients to be able to interpret and react to the data from an MB. CONCLUSIONS: HCPs and patients both recognize that an MB could be beneficial and valuable to patients with COPD at high risk for exacerbation, in the short as well as the long term. In particular, they perceived value in supporting self-management of patients with COPD. Stakeholders would be able to use the obtained insights in support of the effective implementation of MBs in COPD patient care, which can potentially improve health care and the overall well-being of patients with COPD.

Sensory equipment for monitoring and assessing the jumping ability of volleyball players.

Purpose: The objective of this research was to develop a sensor device to control and evaluate the jumping ability of elite volleyball athletes and to test its efficacy in a pedagogical experiment. Methods: The study involved determining the pulsometric and respiratory parameters during test loads, indicative of the endurance and speed-strength aspects essential for volleyball performance. Additionally, the necessity for post-training and post-competition jump performance restoration via short-term relaxation exercises was identified. Results: Through the developed computer program, a method for storing maximal vertical jumps in computer memory was established. Furthermore, a technique was developed to determine the functional significance of maximum vertical jump performance among elite volleyball players. Notably, participants in the experimental group, who performed specialized exercises developed within the experimental framework, exhibited discernible progressive improvements compared to the control group participants. Before the experiment, the maximum number of jumps in the experimental group was 29.2 ± 2.73, with a jump time of 31.7 ± 3.08. Conclusions: The equipment developed for monitoring and assessing volleyball players' jumping ability has proven effective, warranting its incorporation into training regimens.

Hybrid Integration of Wearable Devices for Physiological Monitoring.

Wearable devices can provide timely, user-friendly, non- or minimally invasive, and continuous monitoring of human health. Recently, multidisciplinary scientific communities have made significant progress regarding fully integrated wearable devices such as sweat wearable sensors, saliva sensors, and wound sensors. However, the translation of these wearables into markets has been slow due to several reasons associated with the poor system-level performance of integrated wearables. The wearability consideration for wearable devices compromises many properties of the wearables. Besides, the limited power capacity of wearables hinders continuous monitoring for extended duration. Furthermore, peak-power operations for intensive computations can quickly create thermal issues in the compact form factor that interfere with wearability and sensor operations. Moreover, wearable devices are constantly subjected to environmental, mechanical, chemical, and electrical interferences and variables that can invalidate the collected data. This generates the need for sophisticated data analytics to contextually identify, include, and exclude data points per multisensor fusion to enable accurate data interpretation. This review synthesizes the challenges surrounding the wearable device integration from three aspects in terms of hardware, energy, and data, focuses on a discussion about hybrid integration of wearable devices, and seeks to provide comprehensive guidance for designing fully functional and stable wearable devices.

Is It Possible to Monitor the Safest Time to Perform Secondary Surgery on Free Flaps? A Clinical Evaluation of the Tewameter®.

Background and Objectives: Postoperative monitoring, following free flap surgery, plays a crucial role in ensuring the survival of the flap. However, in microsurgery, not only the immediate postoperative monitoring period but also the choice of the right time for secondary surgeries is crucial for the free flap survival. There is no clear consensus concerning the right choice of timing for secondary surgery. Our aim was to evaluate transepidermal water loss (TEWL), with the objective evaluation tool Tewameter® in free flap surgery to monitor flap autonomization. Materials and Methods: Transepidermal water loss was assessed in 20 patients with microsurgically transplanted free anterior lateral thigh (ALTP) flaps. The transplantation of the ALTP-flap and the postoperative care were administered in accordance with the standard of care of the department. Measures were taken on the free flap and normal skin at follow-ups of 1, 3, and 6 months after initial free flap transplantation. Results: Transepidermal water loss gradually increased to the values found in normal skin, after 6 months. The differences between the two areas demonstrated the smallest variance after 6 months, specifically in the ALTP-flap region. The largest disparities were observed between month 1 and month 6, followed by month 3 and month 6, and month 1 and month 3. Conclusions: Free flap autonomization and physiology are complex processes. TEWL might be a valuable parameter to monitor flap autonomization. Our results indicate that TEWL in the free flap is nearly "normal" after six months. For a clear consensus of when to perform individual secondary surgery, further studies are needed.