A deep learning–enabled smart garment for accurate and versatile monitoring of sleep conditions in daily life DOI Creative Commons
Chenyu Tang,

Wentian Yi,

Muzi Xu

и другие.

Proceedings of the National Academy of Sciences, Год журнала: 2025, Номер 122(7)

Опубликована: Фев. 11, 2025

In wearable smart systems, continuous monitoring and accurate classification of different sleep-related conditions are critical for enhancing sleep quality preventing chronic conditions. However, the requirements device–skin coupling in electrophysiological systems hinder comfort reliability night wearing. Here, we report a washable, skin-compatible garment system that captures local skin strain signals under weak without positioning or preparation requirements. A printed textile-based sensor array responds to from 0.1 10% with gauge factor as high 100 shows independence extrinsic motion artifacts via strain-isolating pattern design. Through reversible starching treatment, ink penetration depth during direct printing on garments is controlled achieve batch-to-batch performance variation <10%. Coupled deep learning, explainable AI, transfer learning data processing, capable classifying six states an accuracy 98.6%, maintaining excellent explainability (classification low bias) generalization (95% new users few-shot less than 15 samples per class) practical applications, paving way next-generation daily healthcare management.

Язык: Английский

Trends in Workplace Wearable Technologies and Connected‐Worker Solutions for Next‐Generation Occupational Safety, Health, and Productivity DOI Creative Commons
Vishal Patel,

Austin Chesmore,

Christopher Legner

и другие.

Advanced Intelligent Systems, Год журнала: 2021, Номер 4(1)

Опубликована: Сен. 23, 2021

The workplace influences the safety, health, and productivity of workers at multiple levels. To protect promote total worker smart hardware, software tools have emerged for identification, elimination, substitution, control occupational hazards. Wearable devices enable constant monitoring individual environment, whereas connected solutions provide contextual information decision support. Here, recent trends in commercial technologies to monitor manage risks, injuries, accidents, diseases are reviewed. Workplace safety wearables safe lifting, ergonomics, hazard sleep monitoring, fatigue management, heat cold stress discussed. Examples asset tracking, augmented reality, gesture motion control, brain wave sensing, work management given. health designed work-related musculoskeletal disorders, functional movement respiratory hazards, cardiovascular outdoor sun exposure, continuous glucose shown. Connected platforms discussed with about architecture, system modules, intelligent operations, industry applications. Predictive analytics resource allocation, equipment failure, predictive maintenance. Altogether, these examples highlight ground-level benefits real-time visibility frontline workers, distributed assets, workforce efficiency, compliance

Язык: Английский

Процитировано

159

Smartwatches in healthcare medicine: assistance and monitoring; a scoping review DOI Creative Commons
Mohsen Masoumian Hosseini, Seyedeh Toktam Masoumian Hosseini,

Karim Qayumi

и другие.

BMC Medical Informatics and Decision Making, Год журнала: 2023, Номер 23(1)

Опубликована: Ноя. 3, 2023

Abstract Smartwatches have become increasingly popular in recent times because of their capacity to track different health indicators, including heart rate, patterns sleep, and physical movements. This scoping review aims explore the utilisation smartwatches within healthcare sector. According Arksey O'Malley's methodology, an organised search was performed PubMed/Medline, Scopus, Embase, Web Science, ERIC Google Scholar. In our strategy, 761 articles were returned. The exclusion/inclusion criteria applied. Finally, 35 selected for extracting data. These included six studies on stress monitoring, movement disorders, three sleep tracking, blood pressure, two disease, covid pandemic, safety validation. use has been found be effective diagnosing symptoms various diseases. particular, shown promise detecting diseases, even early signs COVID-19. Nevertheless, it should emphasised that there is ongoing discussion concerning reliability smartwatch diagnoses systems. Despite potential advantages offered by utilising disease detection, imperative approach data interpretation with prudence. discrepancies detection between algorithms important implications use. accuracy used are crucial, as well high changes status themselves. calls development medical watches creation AI-hospital assistants. assistants will designed help patient appointment scheduling, medication management tasks. They can educate patients answer common questions, freeing providers focus more complex

Язык: Английский

Процитировано

77

ChatDiet: Empowering personalized nutrition-oriented food recommender chatbots through an LLM-augmented framework DOI Creative Commons
Zhongqi Yang, Elahe Khatibi, Nitish Nagesh

и другие.

Smart Health, Год журнала: 2024, Номер 32, С. 100465 - 100465

Опубликована: Март 24, 2024

Язык: Английский

Процитировано

22

Accuracy Assessment of Oura Ring Nocturnal Heart Rate and Heart Rate Variability in Comparison With Electrocardiography in Time and Frequency Domains: Comprehensive Analysis DOI Creative Commons
Rui Cao, Iman Azimi, Fatemeh Sarhaddi

и другие.

Journal of Medical Internet Research, Год журнала: 2021, Номер 24(1), С. e27487 - e27487

Опубликована: Ноя. 9, 2021

Background Photoplethysmography is a noninvasive and low-cost method to remotely continuously track vital signs. The Oura Ring compact photoplethysmography-based smart ring, which has recently drawn attention remote health monitoring wellness applications. ring used acquire nocturnal heart rate (HR) HR variability (HRV) parameters ubiquitously. However, these are highly susceptible motion artifacts environmental noise. Therefore, validity assessment of the required in everyday settings. Objective This study aims evaluate accuracy time domain frequency HRV collected by against medical grade chest electrocardiogram monitor. Methods We conducted overnight home-based using an Shimmer3 device. 35 healthy individuals were assessed. evaluated within 2 tests, that is, values from 5-minute recordings (ie, short-term analysis) average per night sleep. A linear regression method, Pearson correlation coefficient, Bland–Altman plot compare measurements devices. Results Our findings showed low mean biases both average-per-night tests. In test, error variances different. provided dashboard root square successive differences [RMSSD]) relatively variance compared with extracted normal interbeat interval signals. coefficient tests (P<.001) indicated HR, RMSSD, beat intervals (AVNN), percentage beat-to-beat differ more than 50 ms (pNN50) had high positive correlations baseline values; SD (SDNN) (HF) moderate correlations, (LF) LF:HF ratio correlations. AVNN, pNN50 narrow 95% CIs; however, SDNN, LF, HF, wider CIs. contrast, test pNN50, HF relationships (P<.001), relationship (P<.001). also considerably lower for parameters. Conclusions could accurately measure RMSSD It acceptable SDNN but not test. LF rates

Язык: Английский

Процитировано

84

Long-Term IoT-Based Maternal Monitoring: System Design and Evaluation DOI Creative Commons
Fatemeh Sarhaddi, Iman Azimi, Sina Labbaf

и другие.

Sensors, Год журнала: 2021, Номер 21(7), С. 2281 - 2281

Опубликована: Март 24, 2021

Pregnancy is a unique time when many mothers gain awareness of their lifestyle and its impacts on the fetus. High-quality care during pregnancy needed to identify possible complications early ensure mother’s her unborn baby’s health well-being. Different studies have thus far proposed maternal monitoring systems. However, they are designed for specific problem or limited questionnaires short-term data collection methods. Moreover, requirements challenges not been evaluated in long-term studies. Maternal necessitates comprehensive framework enabling continuous pregnant women. In this paper, we present an Internet-of-Things (IoT)-based system provide ubiquitous postpartum. The consists various collectors track condition, including stress, sleep, physical activity. We carried out full implementation conducted real human subject study women Southwestern Finland. then system’s feasibility, energy efficiency, reliability. Our results show that implemented feasible terms usage nine months. also indicate smartwatch, used our study, has acceptable efficiency able collect reliable photoplethysmography data. Finally, discuss integration presented with current healthcare system.

Язык: Английский

Процитировано

72

Human NREM Sleep Promotes Brain-Wide Vasomotor and Respiratory Pulsations DOI Creative Commons
Heta Helakari, Vesa Korhonen, Sebastian C. Holst

и другие.

Journal of Neuroscience, Год журнала: 2022, Номер 42(12), С. 2503 - 2515

Опубликована: Фев. 8, 2022

The physiological underpinnings of the necessity sleep remain uncertain. Recent evidence suggests that increases convection cerebrospinal fluid (CSF) and promotes export interstitial solutes, thus providing a framework to explain why all vertebrate species require sleep. Cardiovascular, respiratory vasomotor brain pulsations have each been shown drive CSF flow along perivascular spaces, yet it is unknown how such may change during in humans. To investigate these pulsation phenomena relation sleep, we simultaneously recorded fast fMRI, magnetic resonance encephalography (MREG), electroencephalography (EEG) signals group healthy volunteers. We quantified sleep-related changes signal frequency distributions by spectral entropy analysis calculated strength (vasomotor, respiratory, cardiac) power sum 15 subjects (age 26.5 ± 4.2 years, 6 females). Finally, identified spatial similarities between EEG slow oscillation (0.2–2 Hz) MREG pulsations. Compared with wakefulness, nonrapid eye movement (NREM) was characterized reduced increased intensity. These effects were most pronounced posterior areas for very low-frequency (≤0.1 but also evident brain-wide pulsations, lesser extent cardiac There regions spatially overlapping those showing changes. suggest enhanced intensity are characteristic NREM With our findings oscillation, present results support proposition transport human brain. SIGNIFICANCE STATEMENT report mechanisms driven vasomotor, respiration, rhythms increase extending previous observations their association glymphatic clearance rodents. magnitudes follow rank order greater than correspondingly declining extents. Spectral entropy, previously known as vigilance an anesthesia metric, decreased compared awake state low frequencies, indicating complexity. An occurring early phase (NREM 1–2) overlapped changes, reciprocal measures.

Язык: Английский

Процитировано

64

Emognition dataset: emotion recognition with self-reports, facial expressions, and physiology using wearables DOI Creative Commons
Stanisław Saganowski, Joanna Komoszyńska, Maciej Behnke

и другие.

Scientific Data, Год журнала: 2022, Номер 9(1)

Опубликована: Апрель 7, 2022

Abstract The Emognition dataset is dedicated to testing methods for emotion recognition (ER) from physiological responses and facial expressions. We collected data 43 participants who watched short film clips eliciting nine discrete emotions: amusement, awe, enthusiasm, liking, surprise, anger, disgust, fear, sadness. Three wearables were used record data: EEG, BVP (2x), HR, EDA, SKT, ACC (3x), GYRO (2x); in parallel with the upper-body videos. After each clip, completed two types of self-reports: (1) related emotions (2) three affective dimensions: valence, arousal, motivation. obtained facilitates various ER approaches, e.g., multimodal ER, EEG- vs. cardiovascular-based dimensional representation transitions. technical validation indicated that watching elicited targeted emotions. It also supported signals’ high quality.

Язык: Английский

Процитировано

57

Smart Consumer Wearables as Digital Diagnostic Tools: A Review DOI Creative Commons

Shweta Chakrabarti,

Nupur Biswas, L. Jones

и другие.

Diagnostics, Год журнала: 2022, Номер 12(9), С. 2110 - 2110

Опубликована: Авг. 31, 2022

The increasing usage of smart wearable devices has made an impact not only on the lifestyle users, but also biological research and personalized healthcare services. These devices, which carry different types sensors, have emerged as digital diagnostic tools. Data from such enabled prediction detection various physiological well psychological conditions diseases. In this review, we focused applications wrist-worn wearables to detect multiple diseases cardiovascular diseases, neurological disorders, fatty liver metabolic including diabetes, sleep quality, illnesses. fruitful requires fast insightful data analysis, is feasible through machine learning. discussed machine-learning outcomes for analyses. Finally, current challenges with data, future perspectives tools domains.

Язык: Английский

Процитировано

42

The Importance of Nutrition in Menopause and Perimenopause—A Review DOI Open Access

Aliz Erdélyi,

Erzsébet Pálfi, László Tűű

и другие.

Nutrients, Год журнала: 2023, Номер 16(1), С. 27 - 27

Опубликована: Дек. 21, 2023

Menopause is associated with an increased prevalence of obesity, metabolic syndrome, cardiovascular diseases, and osteoporosis. These diseases unfavorable laboratory values, which are characteristic this period in women, can be significantly improved by eliminating reducing dietary risk factors. Changing habits during perimenopause most effectively achieved through nutrition counseling intervention. To reduce the factors all these case already existing disease, therapy led a dietitian should integral part treatment. The following review summarizes recommendations for balanced diet fluid intake, prevention role sleep, key preventive nutrients menopause, such as vitamin D, calcium, C, B vitamins, protein intake. In summary, many lifestyle developing (cardiovascular insulin resistance, type 2 diabetes mellitus, osteoporosis, tumors) symptoms period.

Язык: Английский

Процитировано

38

Influence of next-generation artificial intelligence on headache research, diagnosis and treatment: the junior editorial board members’ vision – part 2 DOI Creative Commons
Igor Petrušić, Chia‐Chun Chiang, David García‐Azorín

и другие.

The Journal of Headache and Pain, Год журнала: 2025, Номер 26(1)

Опубликована: Янв. 2, 2025

Part 2 explores the transformative potential of artificial intelligence (AI) in addressing complexities headache disorders through innovative approaches, including digital twin models, wearable healthcare technologies and biosensors, AI-driven drug discovery. Digital twins, as dynamic representations patients, offer opportunities for personalized management by integrating diverse datasets such neuroimaging, multiomics, sensor data to advance research, optimize treatment, enable virtual trials. In addition, devices equipped with next-generation biosensors combined multi-agent chatbots could real-time physiological biochemical monitoring, diagnosing, facilitating early attack forecasting prevention, disease tracking, interventions. Furthermore, advances discovery leverage machine learning generative AI accelerate identification novel therapeutic targets treatment strategies migraine other disorders. Despite these advances, challenges standardization, model explainability, ethical considerations remain pivotal. Collaborative efforts between clinicians, biomedical biotechnological engineers, scientists, legal representatives bioethics experts are essential overcoming barriers unlocking AI's full transforming research healthcare. This is a call action proposing frameworks AI-based into care.

Язык: Английский

Процитировано

2