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1.
J Healthc Eng ; 2023: 6172812, 2023.
Article in English | MEDLINE | ID: mdl-36698847

ABSTRACT

Background: Lateral thrust seen in people with medial compartment knee osteoarthritis can cause dynamic knee instability and poor postural control during gait cycles. A lateral wedge insole can reduce the lateral thrust and may have a favorable effect on gait variability, which in turn may indicate gait instability improves. The aim of this study was to investigate the effect of lateral wedge insole on gait variability in knee osteoarthritis patients. Method: We involved 15 symptomatic knee osteoarthritis patients who were provided with lateral wedge insole and 13 healthy asymptomatic volunteers as the control group. The gait variability was evaluated as the coefficient of variation of stride, stance, and swing duration based on acceleration monitoring using a wearable sensor. The lateral thrust was estimated as the lateral acceleration peak on the shank sensor. These measurements were performed without lateral wedge insole (baseline), immediately with lateral wedge insole (T0) at the initial office visit and one month after intervention (T1). Result: Our data showed that the stance duration coefficient of variation and lateral thrust at T1 in the knee osteoarthritis group, were significantly decreased compared to the baseline values and these values were identical to those in the control group. Conclusion: The lateral wedge insole reduces dynamic knee instability and could improve gait variability in medial compartment knee osteoarthritis.


Subject(s)
Joint Instability , Osteoarthritis, Knee , Wearable Electronic Devices , Humans , Knee Joint , Gait , Shoes , Biomechanical Phenomena
2.
Front Public Health ; 10: 1035398, 2022.
Article in English | MEDLINE | ID: mdl-36699866

ABSTRACT

Introduction: As the proportion of the world's elderly population continues to increase, wearable devices can provide ideas for solving a series of problems caused by population aging. Therefore, it is of great significance for the development of intelligent elderly care and the improvement of the quality of elderly care services to explore the factors that influence the intention of elderly users to accept wearable devices. Methods: An improved unified theory of acceptance and use of technology (UTAUT) model is constructed from the perspective of elderly individuals, and new parameters are added, including four factors related to wearable devices, including performance expectancy, perceived cost, hedonic value and aesthetic appeal, and three factors related to elderly individuals, including personal physiological conditions, health anxiety and personal innovativeness in information technology. The data analysis was accomplished with the partial least square regression structural equation modeling. Results: The findings of this study revealed that performance expectancy, perceived cost, hedonic value and aesthetic appeal all have significant impact on elderly users' intention to use wearable devices. Furthermore, personal innovativeness in information technology, personal physiological condition, and intention to use all have significant impact on elderly users' actual usage behavior of wearable devices. However, there is no obvious relationship between health anxiety and actual usage behavior. Discussion: Elderly adults' attention to wearable devices plays an important role in the development of the wearable device-related industry chain, which provides management suggestions for stakeholders.


Subject(s)
Intention , Wearable Electronic Devices , Adult , Humans , Aged , Anxiety , Technology , Anxiety Disorders
3.
J Med Internet Res ; 25: e40529, 2023 Jan 25.
Article in English | MEDLINE | ID: mdl-36696172

ABSTRACT

BACKGROUND: There is some initial evidence suggesting that mindsets about the adequacy and health consequences of one's physical activity (activity adequacy mindsets [AAMs]) can shape physical activity behavior, health, and well-being. However, it is unknown how to leverage these mindsets using wearable technology and other interventions. OBJECTIVE: This research examined how wearable fitness trackers and meta-mindset interventions influence AAMs, affect, behavior, and health. METHODS: A total of 162 community-dwelling adults were recruited via flyers and web-based platforms (ie, Craigslist and Nextdoor; final sample size after attrition or exclusion of 45 participants). Participants received an Apple Watch (Apple Inc) to wear for 5 weeks, which was equipped with an app that recorded step count and could display a (potentially manipulated) step count on the watch face. After a baseline week of receiving no feedback about step count, participants were randomly assigned to 1 of 4 experimental groups: they received either accurate step count (reference group; 41/162, 25.3%), 40% deflated step count (40/162, 24.7%), 40% inflated step count (40/162, 24.7%), or accurate step count+a web-based meta-mindset intervention teaching participants the value of adopting more positive AAMs (41/162, 25.3%). Participants were blinded to the condition. Outcome measures were taken in the laboratory by an experimenter at the beginning and end of participation and via web-based surveys in between. Longitudinal analysis examined changes within the accurate step count condition from baseline to treatment and compared them with changes in the deflated step count, inflated step count, and meta-mindset conditions. RESULTS: Participants receiving accurate step counts perceived their activity as more adequate and healthier, adopted a healthier diet, and experienced improved mental health (Patient-Reported Outcomes Measurement Information System [PROMIS]-29) and aerobic capacity but also reduced functional health (PROMIS-29; compared with their no-step-count baseline). Participants exposed to deflated step counts perceived their activity as more inadequate; ate more unhealthily; and experienced more negative affect, reduced self-esteem and mental health, and increased blood pressure and heart rate (compared with participants receiving accurate step counts). Inflated step counts did not change AAM or most other outcomes (compared with accurate step counts). Participants receiving the meta-mindset intervention experienced improved AAM, affect, functional health, and self-reported physical activity (compared with participants receiving accurate step counts only). Actual step count did not change in either condition. CONCLUSIONS: AAMs--induced by trackers or adopted deliberately--can influence affect, behavior, and health independently of actual physical activity. TRIAL REGISTRATION: ClinicalTrials.gov NCT03939572; https://www.clinicaltrials.gov/ct2/show/NCT03939572.


Subject(s)
Fitness Trackers , Wearable Electronic Devices , Adult , Humans , Exercise/psychology , Motor Activity , Outcome Assessment, Health Care
4.
Nature ; 613(7945): 667-675, 2023 Jan.
Article in English | MEDLINE | ID: mdl-36697864

ABSTRACT

Continuous imaging of cardiac functions is highly desirable for the assessment of long-term cardiovascular health, detection of acute cardiac dysfunction and clinical management of critically ill or surgical patients1-4. However, conventional non-invasive approaches to image the cardiac function cannot provide continuous measurements owing to device bulkiness5-11, and existing wearable cardiac devices can only capture signals on the skin12-16. Here we report a wearable ultrasonic device for continuous, real-time and direct cardiac function assessment. We introduce innovations in device design and material fabrication that improve the mechanical coupling between the device and human skin, allowing the left ventricle to be examined from different views during motion. We also develop a deep learning model that automatically extracts the left ventricular volume from the continuous image recording, yielding waveforms of key cardiac performance indices such as stroke volume, cardiac output and ejection fraction. This technology enables dynamic wearable monitoring of cardiac performance with substantially improved accuracy in various environments.


Subject(s)
Heart , Wearable Electronic Devices , Humans , Heart/diagnostic imaging , Stroke Volume , Echocardiography , Heart Ventricles , Cardiac Output
5.
Sensors (Basel) ; 23(2)2023 Jan 04.
Article in English | MEDLINE | ID: mdl-36679371

ABSTRACT

The improvement of comfort monitoring resources is pivotal for a better understanding of personal perception in indoor and outdoor environments and thus developing personalized comfort models maximizing occupants' well-being while minimizing energy consumption. Different daily routines and their relation to the thermal sensation remain a challenge in long-term monitoring campaigns. This paper presents a new methodology to investigate the correlation between individuals' daily Thermal Sensation Vote (TSV) and environmental exposure. Participants engaged in the long-term campaign were instructed to answer a daily survey about thermal comfort perception and wore a device continuously monitoring temperature and relative humidity in their surroundings. Normalized daily profiles of monitored variables and calculated heat index were clustered to identify common exposure profiles for each participant. The correlation between each cluster and expressed TSV was evaluated through the Kendall tau-b test. Most of the significant correlations were related to the heat index profiles, i.e., 49% of cases, suggesting that a more detailed description of physical boundaries better approximates expressed comfort. This research represents the first step towards personalized comfort models accounting for individual long-term environmental exposure. A longer campaign involving more participants should be organized in future studies, involving also physiological variables for energy-saving purposes.


Subject(s)
Benchmarking , Wearable Electronic Devices , Humans , Thermosensing , Temperature , Perception
6.
Sensors (Basel) ; 23(2)2023 Jan 05.
Article in English | MEDLINE | ID: mdl-36679418

ABSTRACT

Wearable devices have been shown to play an important role in disease prevention and health management, through the multimodal acquisition of peripheral biosignals. However, many of these wearables are exposed, limiting their long-term acceptability by some user groups. To overcome this, a wearable smart sock integrating a PPG sensor and an EDA sensor with textile electrodes was developed. Using the smart sock, EDA and PPG measurements at the foot/ankle were performed in test populations of 19 and 15 subjects, respectively. Both measurements were validated by simultaneously recording the same signals with a standard device at the hand. For the EDA measurements, Pearson correlations of up to 0.95 were obtained for the SCL component, and a mean consensus of 69% for peaks detected in the two locations was obtained. As for the PPG measurements, after fine-tuning the automatic detection of systolic peaks, the index finger and ankle, accuracies of 99.46% and 87.85% were obtained, respectively. Moreover, an HR estimation error of 17.40±14.80 Beats-Per-Minute (BPM) was obtained. Overall, the results support the feasibility of this wearable form factor for unobtrusive EDA and PPG monitoring.


Subject(s)
Galvanic Skin Response , Wearable Electronic Devices , Humans , Photoplethysmography/methods , Feasibility Studies , Foot , Heart Rate
7.
Sensors (Basel) ; 23(2)2023 Jan 05.
Article in English | MEDLINE | ID: mdl-36679424

ABSTRACT

The restoration of gait and mobility after stroke is an important and challenging therapy goal due to the complexity of the potentially impaired functions. As a result, precise and clinically feasible assessment methods are required for personalized gait rehabilitation after stroke. The aim of this study is to investigate the reliability and validity of a sensor-based gait analysis system in stroke survivors with different severities of gait deficits. For this purpose, 28 chronic stroke survivors (9 women, ages: 62.04 ± 11.68 years) with mild to moderate walking impairments performed a set of ambulatory assessments (3× 10MWT, 1× 6MWT per session) twice while being equipped with a sensor suit. The derived gait reports provided information about speed, step length, step width, swing and stance phases, as well as joint angles of the hip, knee, and ankle, which we analyzed for test-retest reliability and hypothesis testing. Further, test-retest reliability resulted in a mean ICC of 0.78 (range: 0.46-0.88) for walking 10 m and a mean ICC of 0.90 (range: 0.63-0.99) for walking 6 min. Additionally, all gait parameters showed moderate-to-strong correlations with clinical scales reflecting lower limb function. These results support the applicability of this sensor-based gait analysis system for individuals with stroke-related walking impairments.


Subject(s)
Stroke Rehabilitation , Stroke , Wearable Electronic Devices , Humans , Female , Middle Aged , Aged , Gait Analysis , Reproducibility of Results , Gait , Walking
8.
Sensors (Basel) ; 23(2)2023 Jan 06.
Article in English | MEDLINE | ID: mdl-36679484

ABSTRACT

Few studies have dealt with lower-limb kinematics during the timed up and go (TUG) test in subjects with locomotive syndrome (LS). This study aimed to evaluate the characteristics of lower-limb kinematics during the TUG test in subjects with LS using the wearable sensor-based H-Gait system. A total of 140 participants were divided into the non-LS (n = 28), the LS-stage 1 (n = 78), and LS-stage 2 (n = 34) groups based on the LS risk test. Compared with the non-LS group, the LS-stage 1 and LS-stage 2 groups showed significantly smaller angular velocity of hip and knee extension during the sit-to-stand phase. The LS-stage 2 group showed significantly smaller peak angles of hip extension and flexion during the walking-out phase compared to the non-LS group. These findings indicate that the evaluation of the lower-limb kinematics during the TUG test using the H-Gait system is highly sensitive to detect LS, compared with the evaluation of the lower-limb kinematics when simply walking.


Subject(s)
Gait , Wearable Electronic Devices , Humans , Biomechanical Phenomena , Walking , Lower Extremity
9.
Sensors (Basel) ; 23(2)2023 Jan 07.
Article in English | MEDLINE | ID: mdl-36679492

ABSTRACT

Designing highly active material to fabricate a high-performance noninvasive wearable glucose sensor was of great importance for diabetes monitoring. In this work, we developed CuxO nanoflakes (NFs)/Cu nanoparticles (NPs) nanocomposites to serve as the sensing materials for noninvasive sweat-based wearable glucose sensors. We involve CuCl2 to enhance the oxidation of Cu NPs to generate Cu2O/CuO NFs on the surface. Due to more active sites endowed by the CuxO NFs, the as-prepared sample exhibited high sensitivity (779 µA mM-1 cm-2) for noninvasive wearable sweat sensing. Combined with a low detection limit (79.1 nM), high selectivity and the durability of bending and twisting, the CuxO NFs/Cu NPs-based sensor can detect the glucose level change of sweat in daily life. Such a high-performance wearable sensor fabricated by a convenient method provides a facile way to design copper oxide nanomaterials for noninvasive wearable glucose sensors.


Subject(s)
Biosensing Techniques , Nanocomposites , Nanoparticles , Wearable Electronic Devices , Nanocomposites/chemistry , Copper/chemistry , Glucose/chemistry
10.
Sensors (Basel) ; 23(2)2023 Jan 09.
Article in English | MEDLINE | ID: mdl-36679546

ABSTRACT

Human gait activity recognition is an emerging field of motion analysis that can be applied in various application domains. One of the most attractive applications includes monitoring of gait disorder patients, tracking their disease progression and the modification/evaluation of drugs. This paper proposes a robust, wearable gait motion data acquisition system that allows either the classification of recorded gait data into desirable activities or the identification of common risk factors, thus enhancing the subject's quality of life. Gait motion information was acquired using accelerometers and gyroscopes mounted on the lower limbs, where the sensors were exposed to inertial forces during gait. Additionally, leg muscle activity was measured using strain gauge sensors. As a matter of fact, we wanted to identify different gait activities within each gait recording by utilizing Machine Learning algorithms. In line with this, various Machine Learning methods were tested and compared to establish the best-performing algorithm for the classification of the recorded gait information. The combination of attention-based convolutional and recurrent neural networks algorithms outperformed the other tested algorithms and was individually tested further on the datasets of five subjects and delivered the following averaged results of classification: 98.9% accuracy, 96.8% precision, 97.8% sensitivity, 99.1% specificity and 97.3% F1-score. Moreover, the algorithm's robustness was also verified with the successful detection of freezing gait episodes in a Parkinson's disease patient. The results of this study indicate a feasible gait event classification method capable of complete algorithm personalization.


Subject(s)
Quality of Life , Wearable Electronic Devices , Humans , Gait , Algorithms , Machine Learning
11.
Sensors (Basel) ; 23(2)2023 Jan 09.
Article in English | MEDLINE | ID: mdl-36679563

ABSTRACT

In an increasingly interconnected world, where electronic devices permeate every aspect of our lives, wearable systems aimed at monitoring physiological signals are rapidly taking over the sport and fitness domain, as well as biomedical fields such as rehabilitation and prosthetics. With the intent of providing a novel approach to the field, in this paper we discuss the development of a wearable system for the acquisition of EEG signals based on a portable, low-power custom PCB specifically designed to be used in combination with non-conventional ultra-conformable and imperceptible Parylene-C tattoo electrodes. The proposed system has been tested in a standard rest-state experiment, and its performance in terms of discrimination of two different states has been compared to that of a commercial wearable device for EEG signal acquisition (i.e., the Muse headset), showing comparable results. This first preliminary validation demonstrates the possibility of conveniently employing ultra-conformable tattoo-electrodes integrated portable systems for the unobtrusive acquisition of brain activity.


Subject(s)
Tattooing , Wearable Electronic Devices , Electroencephalography/methods , Electrodes
12.
Sensors (Basel) ; 23(2)2023 Jan 10.
Article in English | MEDLINE | ID: mdl-36679588

ABSTRACT

Aging is one of the greatest challenges in modern society. The development of wearable solutions for telemonitoring biological signals has been viewed as a strategy to enhance older adults' healthcare sustainability. This study aims to review the biological signals remotely monitored by technologies in older adults. PubMed, the Cochrane Database of Systematic Reviews, the Web of Science, and the Joanna Briggs Institute Database of Systematic Reviews and Implementation Reports were systematically searched in December 2021. Only systematic reviews and meta-analyses of remote health-related biological and environmental monitoring signals in older adults were considered, with publication dates between 2016 and 2022, written in English, Portuguese, or Spanish. Studies referring to conference proceedings or articles with abstract access only were excluded. The data were extracted independently by two reviewers, using a predefined table form, consulting a third reviewer in case of doubts or concerns. Eighteen studies were included, fourteen systematic reviews and four meta-analyses. Nine of the reviews included older adults from the community, whereas the others also included institutionalized participants. Heart and respiratory rate, physical activity, electrocardiography, body temperature, blood pressure, glucose, and heart rate were the most frequently measured biological variables, with physical activity and heart rate foremost. These were obtained through wearables, with the waist, wrist, and ankle being the most mentioned body regions for the device's placement. Six of the reviews presented the psychometric properties of the systems, most of which were valid and accurate. In relation to environmental signals, only two articles presented data on this topic. Luminosity, temperature, and movement were the most mentioned variables. The need for large-scale long-term health-related telemonitoring implementation of studies with larger sample sizes was pointed out by several reviews in order to define the feasibility levels of wearable devices.


Subject(s)
Hospitalization , Wearable Electronic Devices , Humans , Aged , Systematic Reviews as Topic , Monitoring, Physiologic , Exercise
13.
Sensors (Basel) ; 23(2)2023 Jan 11.
Article in English | MEDLINE | ID: mdl-36679623

ABSTRACT

Micro electro-mechanical systems (MEMS) are used to record training and match play of intermittent team sport athletes. Paired with estimates of internal responses or adaptations to exercise, practitioners gain insight into players' dose-response relationship which facilitates the prescription of the training stimuli to optimize performance, prevent injuries, and to guide rehabilitation processes. A systematic review on the relationship between external, wearable-based, and internal parameters in team sport athletes, compliant with the PRISMA guidelines, was conducted. The literature research was performed from earliest record to 1 September 2020 using the databases PubMed, Web of Science, CINAHL, and SportDISCUS. A total of 66 full-text articles were reviewed encompassing 1541 athletes. About 109 different relationships between variables have been reviewed. The most investigated relationship across sports was found between (session) rating of perceived exertion ((session-)RPE) and PlayerLoad™ (PL) with, predominantly, moderate to strong associations (r = 0.49-0.84). Relationships between internal parameters and highly dynamic, anaerobic movements were heterogenous. Relationships between average heart rate (HR), Edward's and Banister's training impulse (TRIMP) seem to be reflected in parameters of overall activity such as PL and TD for running-intensive team sports. PL may further be suitable to estimate the overall subjective perception. To identify high fine-structured loading-relative to a certain type of sport-more specific measures and devices are needed. Individualization of parameters could be helpful to enhance practicality.


Subject(s)
Running , Wearable Electronic Devices , Humans , Physical Exertion/physiology , Athletes , Running/physiology , Team Sports
14.
Sensors (Basel) ; 23(2)2023 Jan 11.
Article in English | MEDLINE | ID: mdl-36679632

ABSTRACT

The human radial artery pulse carries a rich array of biomedical information. Accurate detection of pulse signal waveform and the identification of the corresponding pulse condition are helpful in understanding the health status of the human body. In the process of pulse detection, there are some problems, such as inaccurate location of radial artery key points, poor signal noise reduction effect and low accuracy of pulse recognition. In this system, the pulse signal waveform is collected by the main control circuit and the new piezoelectric sensor array combined with the wearable wristband, creating the hardware circuit. The key points of radial artery are located by an adaptive pulse finding algorithm. The pulse signal is denoised by wavelet transform, iterative sliding window and prediction reconstruction algorithm. The slippery pulse and the normal pulse are recognized by feature extraction and classification algorithm, so as to analyze the health status of the human body. The system has accurate pulse positioning, good noise reduction effect, and the accuracy of intelligent analysis is up to 98.4%, which can meet the needs of family health care.


Subject(s)
Wearable Electronic Devices , Wrist , Humans , Heart Rate , Radial Artery , Vital Signs , Pulse
15.
Sensors (Basel) ; 23(2)2023 Jan 11.
Article in English | MEDLINE | ID: mdl-36679626

ABSTRACT

Background: The advancement of information and communication technologies and the growing power of artificial intelligence are successfully transforming a number of concepts that are important to our daily lives. Many sectors, including education, healthcare, industry, and others, are benefiting greatly from the use of such resources. The healthcare sector, for example, was an early adopter of smart wearables, which primarily serve as diagnostic tools. In this context, smart wearables have demonstrated their effectiveness in detecting and predicting cardiovascular diseases (CVDs), the leading cause of death worldwide. Objective: In this study, a systematic literature review of smart wearable applications for cardiovascular disease detection and prediction is presented. After conducting the required search, the documents that met the criteria were analyzed to extract key criteria such as the publication year, vital signs recorded, diseases studied, hardware used, smart models used, datasets used, and performance metrics. Methods: This study followed the PRISMA guidelines by searching IEEE, PubMed, and Scopus for publications published between 2010 and 2022. Once records were located, they were reviewed to determine which ones should be included in the analysis. Finally, the analysis was completed, and the relevant data were included in the review along with the relevant articles. Results: As a result of the comprehensive search procedures, 87 papers were deemed relevant for further review. In addition, the results are discussed to evaluate the development and use of smart wearable devices for cardiovascular disease management, and the results demonstrate the high efficiency of such wearable devices. Conclusions: The results clearly show that interest in this topic has increased. Although the results show that smart wearables are quite accurate in detecting, predicting, and even treating cardiovascular disease, further research is needed to improve their use.


Subject(s)
Cardiovascular Diseases , Wearable Electronic Devices , Humans , Cardiovascular Diseases/diagnosis , Artificial Intelligence
16.
Sensors (Basel) ; 23(2)2023 Jan 12.
Article in English | MEDLINE | ID: mdl-36679676

ABSTRACT

BACKGROUND: With the increase in concern for deaths and illness related to the increase in temperature globally, there is a growing need for real-time monitoring of workers for heat stress indicators. The purpose of this study was to determine the usability of the Slate Safety (SS) wearable physiological monitoring system. METHODS: Twenty nurses performed a common task in a moderate or hot environment while wearing the SS device, the Polar 10 monitor, and having taken the e-Celsius ingestible pill. Data from each device was compared for correlation and accuracy. RESULTS: High correlation was determined between the SS wearable device and the Polar 10 system (0.926) and the ingestible pill (0.595). The SS was comfortable to wear and easily monitored multiple participants from a distance. CONCLUSIONS: The Slate Safety wearable device demonstrated accuracy in measuring core temperature and heart rate while not restricting the motion of the worker, and provided a remote monitoring platform for physiological parameters.


Subject(s)
Heat Stress Disorders , Wearable Electronic Devices , Humans , Heart Rate , Body Temperature , Monitoring, Physiologic
17.
Sensors (Basel) ; 23(2)2023 Jan 14.
Article in English | MEDLINE | ID: mdl-36679781

ABSTRACT

The alteration of the hydrostatic pressure gradient in the human body has been associated with changes in human physiology, including abnormal blood flow, syncope, and visual impairment. The focus of this study was to evaluate changes in the resonant frequency of a wearable electromagnetic resonant skin patch sensor during simulated physiological changes observed in aerospace applications. Simulated microgravity was induced in eight healthy human participants (n = 8), and the implementation of lower body negative pressure (LBNP) countermeasures was induced in four healthy human participants (n = 4). The average shift in resonant frequency was -13.76 ± 6.49 MHz for simulated microgravity with a shift in intracranial pressure (ICP) of 9.53 ± 1.32 mmHg, and a shift of 8.80 ± 5.2097 MHz for LBNP with a shift in ICP of approximately -5.83 ± 2.76 mmHg. The constructed regression model to explain the variance in shifts in ICP using the shifts in resonant frequency (R2 = 0.97) resulted in a root mean square error of 1.24. This work demonstrates a strong correlation between sensor signal response and shifts in ICP. Furthermore, this study establishes a foundation for future work integrating wearable sensors with alert systems and countermeasure recommendations for pilots and astronauts.


Subject(s)
Space Flight , Wearable Electronic Devices , Weightlessness , Humans , Space Flight/methods , Posture/physiology , Lower Body Negative Pressure
18.
Sensors (Basel) ; 23(2)2023 Jan 16.
Article in English | MEDLINE | ID: mdl-36679828

ABSTRACT

Standing up from a seated position is a prerequisite for any kind of physical mobility but many older persons have problems with the sit-to-stand (STS) transfer. There are several exosuits available for industrial work, which might be adapted to the needs of older persons to support STS transfers. However, objective measures to quantify and evaluate such systems are needed. The aim of this study was to quantify the possible support of an exosuit during the STS transfer of geriatric patients. Twenty-one geriatric patients with a median age of 82 years (1.-3.Q. 79-84 years) stood up at a normal pace (1) from a chair without using armrests, (2) with using armrests and (3) from a bed with pushing off, each condition with and without wearing an exosuit. Peak angular velocity of the thighs was measured by body-worn sensors. It was higher when standing up with exosuit support from a bed (92.6 (1.-3.Q. 84.3-116.2)°/s versus 79.7 (1.-3.Q. 74.6-98.2)°/s; p = 0.014) and from a chair with armrests (92.9 (1.-3.Q. 78.3-113.0)°/s versus 77.8 (1.-3.Q. 59.3-100.7)°/s; p = 0.089) compared to no support. There was no effect of the exosuit when standing up from a chair without using armrests. In general, it was possible to quantify the support of the exosuit using sensor-measured peak angular velocity. These results suggest that depending on the STS condition, an exosuit can support older persons during the STS transfer.


Subject(s)
Movement , Wearable Electronic Devices , Humans , Aged , Aged, 80 and over , Pilot Projects , Thigh
19.
Sensors (Basel) ; 23(2)2023 Jan 16.
Article in English | MEDLINE | ID: mdl-36679839

ABSTRACT

Embedded hardware systems, such as wearable devices, are widely used for health status monitoring of ageing people to improve their well-being. In this context, it becomes increasingly important to develop portable, easy-to-use, compact, and energy-efficient hardware-software platforms, to enhance the level of usability and promote their deployment. With this purpose an automatic tri-axial accelerometer-based system for postural recognition has been developed, useful in detecting potential inappropriate behavioral habits for the elderly. Systems in the literature and on the market for this type of analysis mostly use personal computers with high computing resources, which are not easily portable and have high power consumption. To overcome these limitations, a real-time posture recognition Machine Learning algorithm was developed and optimized that could perform highly on platforms with low computational capacity and power consumption. The software was integrated and tested on two low-cost embedded platform (Raspberry Pi 4 and Odroid N2+). The experimentation stage was performed on various Machine Learning pre-trained classifiers using data of seven elderly users. The preliminary results showed an activity classification accuracy of about 98% for the four analyzed postures (Standing, Sitting, Bending, and Lying down), with similar accuracy and a computational load as the state-of-the-art classifiers running on personal computers.


Subject(s)
Benchmarking , Wearable Electronic Devices , Humans , Aged , Posture , Software , Algorithms , Accelerometry
20.
Sensors (Basel) ; 23(2)2023 Jan 10.
Article in English | MEDLINE | ID: mdl-36679612

ABSTRACT

The emergence and advancement of flexible electronics have great potential to lead development trends in many fields, such as "smart electronic skin" and wearable electronics. By acting as intermediates to detect a variety of external stimuli or physiological parameters, flexible sensors are regarded as a core component of flexible electronic systems and have been extensively studied. Unlike conventional rigid sensors requiring costly instruments and complicated fabrication processes, flexible sensors can be manufactured by simple procedures with excellent production efficiency, reliable output performance, and superior adaptability to the irregular surface of the surroundings where they are applied. Here, recent studies on flexible sensors for sensing humidity and strain/pressure are outlined, emphasizing their sensory materials, working mechanisms, structures, fabrication methods, and particular applications. Furthermore, a conclusion, including future perspectives and a short overview of the market share in this field, is given for further advancing this field of research.


Subject(s)
Wearable Electronic Devices , Humans , Electronics , Pain , Humidity
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