The DOI matches its Crossref record; 20 of the 20 references it cites were found in a registry or an index.
Validation of the Hexoskin wearable vest during lying, sitting, standing, and walking activities
Abstract
We tested the validity of the Hexoskin wearable vest to monitor heart rate (HR), breathing rate (BR), tidal volume (VT), minute ventilation, and hip motion intensity (HMI) in comparison with laboratory standard devices during lying, sitting, standing, and walking. Twenty healthy young volunteers participated in this study. First, participants walked 6 min on a treadmill at speeds of 1, 3, and 4.5 km/h followed by increasing treadmill grades until 80% of their predicted maximal heart rate. Second, lying, sitting, and standing tasks were performed (5 min each) followed by 6 min of treadmill walking at 80% of their ventilatory threshold. Analysis of each individual's mean values under each resting or exercise condition by the 2 measurement systems revealed low coefficient of variation and high intraclass correlation values for HR, BR, and HMI. The Bland-Altman results from HR, BR, and HMI indicated no deviation of the mean value from zero and relatively small variability about the mean. VT and minute ventilation were provided in arbitrary units by the Hexoskin device; however, relative magnitude of change from Hexoskin closely tracked the laboratory standard method. Hexoskin presented low variability, good agreement, and consistency. The Hexoskin wearable vest was a valid and consistent tool to monitor activities typical of daily living such as different body positions (lying, sitting, and standing) and various walking speeds.
Overview
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
In the citing paper
“very high agreement with respiration rate measured by turbine respirometer (intraclass correlation coefficient >0.95; coefficient of variation <1.4%)”
From A Critical Review of Consumer Wearables, Mobile Applications, and Equipment for Providing Biofeedback, Monitoring Stress, and Sleep in Physically Active Populations (2018) · cites this paper as Villar et al., 2015
In the citing paper
“It has been independently validated (Villar et al., 2015).”
From A Critical Review of Consumer Wearables, Mobile Applications, and Equipment for Providing Biofeedback, Monitoring Stress, and Sleep in Physically Active Populations (2018) · cites this paper as Villar et al., 2015
In the citing paper
“The device demonstrates very high agreement with heart rate measured by ECG (intraclass correlation coefficient >0.95; coefficient of variation <0.8%)”
From A Critical Review of Consumer Wearables, Mobile Applications, and Equipment for Providing Biofeedback, Monitoring Stress, and Sleep in Physically Active Populations (2018) · cites this paper as Villar et al., 2015
In the citing paper
“moderate to very high agreement with hip motion intensity measured using a separate accelerometer placed on the hip (intraclass correlation coefficient 0.80 to 0.96; coefficient of variation <6.4%)”
From A Critical Review of Consumer Wearables, Mobile Applications, and Equipment for Providing Biofeedback, Monitoring Stress, and Sleep in Physically Active Populations (2018) · cites this paper as Villar et al., 2015
Citations
Cites
A new method for detecting anaerobic threshold by gas exchange
Beaver, W. L., Wasserman, K., & Whipp, B. J. (1986) · Journal of Applied Physiology · doi:10.1152/jappl.1986.60.6.2020 · Cited by 4,103
Activity Recognition from User-Annotated Acceleration Data
Bao, L., & Intille, S. S. (2004) · Lecture Notes in Computer Science · doi:10.1007/978-3-540-24646-6_1 · Cited by 3,147
Karantonis, D. M., Narayanan, M. R., Mathie, M. J., Lovell, N. H., & Celler, B. G. (2006) · IEEE Transactions on Information Technology in Biomedicine · doi:10.1109/titb.2005.856864 · Cited by 1,239
Smart wearable systems: Current status and future challenges
Chan, M., Estève, D., Fourniols, J.-Y., Escriba, C., & Campo, E. (2012) · Artificial Intelligence in Medicine · doi:10.1016/j.artmed.2012.09.003 · Cited by 953
A Wearable Health Care System Based on Knitted Integrated Sensors
Paradiso, R., Loriga, G., & Taccini, N. (2005) · IEEE Transactions on Information Technology in Biomedicine · doi:10.1109/titb.2005.854512 · Cited by 729
Wearable Medical Systems for p-Health
Teng, X.-F., Zhang, Y.-T., Poon, C. C. Y., & Bonato, P. (2008) · IEEE Reviews in Biomedical Engineering · doi:10.1109/rbme.2008.2008248 · Cited by 310
Physical activity and prevention of coronary heart disease.
Rocha, E. (2005) · PubMed · Cited by 291
A wearable yarn-based piezo-resistive sensor
Huang, C., Shen, C., Tang, C.-F., & Chang, S.-H. (2007) · Sensors and Actuators A Physical · doi:10.1016/j.sna.2007.10.069 · Cited by 255
Performance Evaluation of Sensing Fabrics for Monitoring Physiological and Biomechanical Variables
Scilingo, E. P., Gemignani, A., Paradiso, R., Taccini, N., Ghelarducci, B., & DeRossi, D. (2005) · IEEE Transactions on Information Technology in Biomedicine · doi:10.1109/titb.2005.854506 · Cited by 247
Rienzo, M. D., Rizzo, F., Parati, G., Brambilla, G., Ferratini, M., & Castiglioni, P. (2005) · Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) · doi:10.1109/iembs.2005.1616161 · Cited by 200
Research works printed but not linked: 4
- Di Rienzo M., 2005, Applicability in daily life and clinical setting. Conf. Proc. IEEE Eng. Med. Biol. Soc., 7, 7167
- Fox S.M., 1971, Ann. Clin. Res., 3, 404
- Lymberis A., 2008, Conf. Proc. IEEE Eng Med. Biol. Soc., 2008, 5270
- Paradiso R., 2005, Stud. Health Technol. Inform., 117, 9
Cited by
Sorted by citations
Items 101–177 of 177
Wilbur, R. E., Griffin, J. S., Sorensen, M., & Furberg, R. (2018) · JMIR Research Protocols · doi:10.2196/10215 · Cited by 7
MIPHAS: Military Performances and Health Analysis System
Laudato, G., Rosa, G., Scalabrino, S., Simeone, J., Picariello, F., Tudosa, I., Vito, L. D., Boldi, F., Torchitti, P., Ceccarelli, R., et al. (2020) · International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC) · doi:10.5220/0008989400002513 · Cited by 8
Nonlinear Least Squares Estimation for Breathing Monitoring Using FMCW Radars
Beltrão, G., Alaee–Kerahroodi, M., Schröeder, U., Tatarinov, D., & R., B. S. M. (2022) · European Radar Conference (EuRAD) · doi:10.23919/eurad50154.2022.9784561 · Cited by 8
A proactive approach to execute targeted particulate matter control measures for construction works
Priyanka, P. R. J., Cheriyan, D., & Choi, J. (2022) · Journal of Cleaner Production · doi:10.1016/j.jclepro.2022.133168 · Cited by 8
Laufer, B., Docherty, P. D., Murray, R., Krueger‐Ziolek, S., Jalal, N. A., Hoeflinger, F., Rupitsch, S. J., Reindl, L. M., & Möeller, K. (2023) · Sensors · doi:10.3390/s23177407 · Cited by 8
Design and Evaluation of a Wearable Single-Lead ECG for Continuous Monitoring
Angelucci, A., Villamar, O. W. P., Agostoni, P., & Aliverti, A. (2023) · IEEE International Conference on Metrology for eXtended Reality, Artificial Intelligence and Neural Engineering (MetroXRAINE) · doi:10.1109/metroxraine58569.2023.10405813 · Cited by 8
Wearable physiological monitoring of physical exercise and mental health: A systematic review
Chen, F., Zhao, L., Pang, L., Zhang, Y., Lü, L., Li, J., & Liu, C. (2025) · Intelligent Sports and Health · doi:10.1016/j.ish.2024.12.006 · Cited by 11
Automatic cough detection via a multi-sensor smart garment using machine learning
Dixon, P. C., Dubeau, S., Roy, J.-F., & Fournier, P.-A. (2025) · Computers in Biology and Medicine · doi:10.1016/j.compbiomed.2025.110192 · Cited by 8
Hardon, H. J., Kerkhof, Y. N. V., Bartelds, B., Kammeraad, J. A. E., & van Deutekom, A. W. (2025) · JMIR Formative Research · doi:10.2196/70835 · Cited by 9
Breathing Monitoring in Soccer: Part I—Validity of Commercial Wearable Sensors
Innocenti, L., Romano, C., Greco, G., Nuccio, S., Bellini, A., Mari, F., Silvestri, S., Schena, E., Sacchetti, M., Massaroni, C., et al. (2024) · Sensors · doi:10.3390/s24144571 · Cited by 7
MacQuarrie, A., Hunter, J. R., Sheridan, S., Hlushak, A., Sutton, C., & Wickham, J. B. (2021) · Simulation in Healthcare The Journal of the Society for Simulation in Healthcare · doi:10.1097/sih.0000000000000613 · Cited by 7
Brunet, J., Wurz, A. J., Hussien, J., Pitman, A., Conte, E., Ennis, J., Herry, C. L., SEELY, A. J. E., & Seely, D. (2022) · Integrative Cancer Therapies · doi:10.1177/15347354221075576 · Cited by 7
Wearables in Sports Cardiology
Beavers, D. L., & Chung, E. H. (2022) · Clinics in Sports Medicine · doi:10.1016/j.csm.2022.02.004 · Cited by 7
Chang, T. P., Azen, C. G., & Sherman, J. M. (2020) · Academic Emergency Medicine · doi:10.1111/acem.13982 · Cited by 7
The Feasibility of Measuring Lung Hyperinflation With a Smart Shirt: An in Vitro Study
Mannée, D. C., van Helvoort, H. A., & de Jongh, F. H. (2020) · IEEE Sensors Journal · doi:10.1109/jsen.2020.3010265 · Cited by 7
Remote Health Monitoring System for Bedbound Patients
Alizadeh, M., Shaker, G. S. A., & Safavi‐Naeini, S. (2020) · IEEE International Conference on Bioinformatics and Bioengineering (BIBE) · doi:10.1109/bibe50027.2020.00136 · Cited by 7
The Physiology of Paragliding Flight at Moderate and Extreme Altitudes
Wilkes, M., MacInnis, M. J., Hawkes, L. A., Massey, H. C., Eglin, C., & Tipton, M. (2017) · High Altitude Medicine & Biology · doi:10.1089/ham.2017.0127 · Cited by 7
Cuffless Blood Pressure Estimation for Activities of Daily Living
Landry, C., Hedge, E. T., Hughson, R. L., Peterson, S. D., & Arami, A. (2020) · Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) · doi:10.1109/embc44109.2020.9175976 · Cited by 7
Hennepe, N. T., Steegh, V. L. J. M., Pouw, M. H., Roukema, J., de Kleuver, M., & Hooff, M. L. V. (2024) · Spine Deformity · doi:10.1007/s43390-024-00938-4 · Cited by 6
Dogan, A., Bishnoi, A., Sowers, R. B., & Hernandez, M. E. (2025) · IEEE Journal of Biomedical and Health Informatics · doi:10.1109/jbhi.2025.3550092 · Cited by 6
Cozzarelli, N. F., Ashkenazi, I., Khan, I. A., Lonner, J. H., Lajam, C. M., Schwarzkopf, R. M., & Rozell, J. C. (2024) · The Journal of Arthroplasty · doi:10.1016/j.arth.2024.05.063 · Cited by 6
Saygin, M., Schoenmakers, M., Gevonden, M. J., & de Geus, E. J. C. (2025) · Psychophysiology · doi:10.1111/psyp.70021 · Cited by 6
Effect of Cloth Masks and N95 Respirators on Maximal Exercise Performance in Collegiate Athletes
Darnell, M. E., Quinn, T. D., Carnahan, S. P., Carpenter, T., Meglino, N., Yorio, P. L., & Doperak, J. M. (2022) · International Journal of Environmental Research and Public Health · doi:10.3390/ijerph19137586 · Cited by 6
Massaroni, C., Romano, C., Nicolò, A., Innocenti, L., Sacchetti, M., & Schena, E. (2022) · IEEE International Workshop on Sport, Technology and Research (STAR) · doi:10.1109/star53492.2022.9859731 · Cited by 6
Remote vital signs monitoring using a mm-wave FMCW radar
Alizadeh, M. (2019) · UWSpace (University of Waterloo) · Cited by 6
Massaroni, C., Sacchetti, M., Romano, C., Schena, E., Innocenti, L., & Nicolò, A. (2023) · IEEE International Workshop on Metrology for Industry 4.0 & IoT (MetroInd4.0&IoT) · doi:10.1109/metroind4.0iot57462.2023.10180148 · Cited by 5
Survey of Wearable Multi-modal Vital Parameters Measurement Systems
Szczęsna, A., Nowak, A., Grabiec, P., Paszkuta, M., Tajstra, M., & Wojciechowska, M. (2016) · Advances in intelligent systems and computing · doi:10.1007/978-3-319-47154-9_37 · Cited by 5
Bläsing, D. (2017) · Zeitschrift für Arbeitswissenschaft · doi:10.1007/s41449-017-0082-7 · Cited by 5
Mendoza, A., Lyden, K. A., Sirard, J. R., STAUDENMAYER, J. W., Tudor-Locke, C. E., & Freedson, P. S. (2019) · Journal for the Measurement of Physical Behaviour · doi:10.1123/jmpb.2018-0035 · Cited by 4
Combining Rhythmic and Morphological ECG Features for Automatic Detection of Atrial Fibrillation
Laudato, G., Boldi, F., Colavita, A. R., Rosa, G., Scalabrino, S., Torchitti, P., Lazich, A., & Oliveto, R. (2020) · International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC) · doi:10.5220/0008982300002513 · Cited by 4
MacEachern, C. B., Esau, T. J., Zaman, Q. U., & Farooque, A. A. (2023) · Smart Agricultural Technology · doi:10.1016/j.atech.2023.100171 · Cited by 4
Chaari, M., Abid, M., Ouakrim, Y., Lahami, M., & Mezghani, N. (2020) · International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC) · doi:10.5220/0009118700002513 · Cited by 4
Human Context Sensing in Smart Cities
Ranjan, J., Griffiths, E., & Whitehouse, K. (2017) · Smart Cities · doi:10.1002/9781119226444.ch11 · Cited by 4
Detection of focal impaired awareness seizures using a biometric shirt
St‐Jean, J., Gharbi, O., Toffa, D. H., Tran, T. P. Y., Robert, M., Nguyen, D. K., & Assi, E. B. (2025) · Epilepsia Open · doi:10.1002/epi4.70099 · Cited by 3
Weber, T., Ferrin, M., Sweeney, F., Ahmed, S., & Sharmin, M. (2020) · IEEE Annual International Computer Software and Applications Conference (COMPSAC) · doi:10.1109/compsac48688.2020.0-212 · Cited by 3
Halidane, C., Bluteau, J., Pillarella, S., & Kirakoya‐Samadoulougou, F. (2023) · International Journal of Health Promotion and Education · doi:10.1080/14635240.2023.2212373 · Cited by 3
E3V-K5: An Authentic Benchmark for Redefining Video-Based Energy Expenditure Estimation
Zhang, S., Jin, L., Wang, Y., Wang, X., Wen, X., Feng, Z., & Song, M. (2024) · Lecture notes in computer science · doi:10.1007/978-3-031-72761-0_24 · Cited by 3
Wearable Sensing in Low-Field (0.55 T) MRI Environment
Muñoz, F., Nayak, K. S., & Khan, Y. (2025) · IEEE Sensors Letters · doi:10.1109/lsens.2025.3528305 · Cited by 3
Revolutionizing Patient Care: AI-Driven Wearable Technology for Continuous Remote Health Monitoring
Bhatia, K., & Hasija, Y. (2025) · International Conference on Cognitive Computing in Engineering, Communications, Sciences and Biomedical Health Informatics (IC3ECSBHI) · doi:10.1109/ic3ecsbhi63591.2025.10990913 · Cited by 3
Technological Advances in Clinical Assessment
Trull, T. J., Griffin, S. A., & Helle, A. C. (2019) · Cambridge University Press eBooks · doi:10.1017/9781108235433.007 · Cited by 3
Laufer, B., Jalal, N. A., Docherty, P. D., Busch, C., Krueger‐Ziolek, S., Hoeflinger, F., Chase, J. G., Reindl, L. M., & Möeller, K. (2023) · IFAC-PapersOnLine · doi:10.1016/j.ifacol.2023.10.351 · Cited by 3
Mindfulness Exercises Reduce Acute Physiologic Stress Among Female Clinicians
Wolfe, A. H. J., Hinds, P. S., du Plessis, A. J., Gordish‐Dressman, H., Freedenberg, V. A., & Soghier, L. M. (2024) · Critical Care Explorations · doi:10.1097/cce.0000000000001171 · Cited by 6
Flexible Bioelectrodes-Integrated Miniaturized System for Unconstrained ECG Monitoring
Zhan, Y., Wang, X., & Yang, J. (2025) · Sensors · doi:10.3390/s25134213 · Cited by 2
Radar-Based Vital Signal Extraction via Morphological Component Analysis
Li, H., Ayuknso, A. G. B., Yang, N., Wei, Z., Zhi, M., Hua, Q., & Zhao, B. (2025) · IEEE Transactions on Microwave Theory and Techniques · doi:10.1109/tmtt.2025.3590047 · Cited by 2
Pečík, M., Vavrinský, E., Vitazkova, D., Kosnacova, H., Nevřela, J., & Foltan, E. (2026) · Biosensors · doi:10.3390/bios16060306 · Cited by 3
Xu, H., Chu, W., Liu, X., Zhang, S., Yang, Z., Zheng, J., Gao, X., Zhang, Z., & Cao, D. (2020) · PubMed Central · doi:10.7507/1001-5515.201903061 · Cited by 2
Yoshiike, T., Yajima, T., Utsumi, T., Tripathi, S., Kawamura, A., Nagao, K., Matsui, K., Matsuda, Y., Abe, M., Ito, M., et al. (2025) · Dialogues in Clinical Neuroscience · doi:10.1080/19585969.2025.2597058 · Cited by 1
Chung, K. Y., Lee, B.-K., Song, K., Shin, K., Cho, S. H., & Chang, J. (2016) · IEEE International Conference on Network Infrastructure and Digital Content (IC-NIDC) · doi:10.1109/icnidc.2016.7974619 · Cited by 1
Comparative Study of Electrocardiogram Signals Acquired from Different Smart Textile Shirts
Nawawi, M. M. M., Sidek, K. A., & Azman, A. W. (2021) · International Conference on Computer and Communication Engineering · doi:10.1109/iccce50029.2021.9467251 · Cited by 1
Comparison Study of Attention Between Training in a Simulator vs. Live-Fire Range
Krätzig, G. P., Hembroff, C. C., & Ahlgrim, B. (2021) · Lecture notes in computer science · doi:10.1007/978-3-030-78114-9_13 · Cited by 1
HİPERTANSİYON HASTALARI İÇİN GİYİLEBİLİR SAĞLIK TEKNOLOJİLERİ SEÇİMİ
Akıncı, B. N., DANIŞAN, T., & Eren, T. (2021) · Hacettepe Üniversitesi Sağlık Bilimleri Fakültesi Dergisi · doi:10.21020/husbfd.767834 · Cited by 1
Updates of Wearing Devices (WDs) In Healthcare, And Disease Monitoring
Naser, M., Nasr, M., & Shehata, L. H. (2023) · International Journal of Progressive Sciences and Technologies · doi:10.52155/ijpsat.v39.1.5361 · Cited by 1
Study on the stability and accuracy of the new Booster portable cardiopulmonary function meter
Yun, H., Zhang, W., Chen, Y., Li, Q., & Song, Y. (2025) · Frontiers in Physiology · doi:10.3389/fphys.2024.1453942 · Cited by 1
Laufer, B., Alshirbaji, T. A., Docherty, P. D., Jalal, N. A., Krueger‐Ziolek, S., & Möeller, K. (2025) · Sensors · doi:10.3390/s25082401 · Cited by 1
Design and Test Strategies for Biopotential Sensors in Smart Garments.
Cobarrubias, E. (2020) · NCSU Libraries Repository (North Carolina State University Libraries) · Cited by 1
Rosa, G., Russodivito, M., Laudato, G., Colavita, A. R., Vito, L. D., Picariello, F., Scalabrino, S., Tudosa, I., & Oliveto, R. (2022) · Communications in computer and information science · doi:10.1007/978-3-031-20664-1_12 · Cited by 1
Amelard, R., Hedge, E. T., & Hughson, R. L. (2021) · arXiv (Cornell University) · Cited by 1
Prediction of Oxygen Uptake and its Dynamics by Wearable Sensors During Activities of Daily Living
Beltrame, T. (2016) · UWSpace (University of Waterloo)
Adaptive Controllers for Assistive Robotic Devices
Koller, J. R. (2017) · Deep Blue (University of Michigan)
Hedge, E. T. (2020) · UWSpace (University of Waterloo)
Symmetry of Respiration Induced Upper Body Movements
Laufer, B., Krueger‐Ziolek, S., Jalal, N. A., Docherty, P. D., Hoeflinger, F., Reindl, L. M., & Möeller, K. (2023) · Current Directions in Biomedical Engineering · doi:10.1515/cdbme-2023-1120
Intradialytic exercise in haemodialysis patients: applicability and effects on muscle function
Zelko, A. (2024) · University of Groningen research database (University of Groningen / Centre for Information Technology) · doi:10.33612/diss.1003141320
Pavan, K., & Ganapathy, N. (2024) · Studies in health technology and informatics · doi:10.3233/shti240568
Hardon, H. J., Kerkhof, Y. N. V., Bartelds, B., Kammeraad, J. A. E., & van Deutekom, A. W. (2025) · doi:10.2196/preprints.70835
Kuznetsov, M., Grant, A. R., Coden, G. S., Travers, H. I., & Talmo, C. T. (2025) · Journal of Orthopaedic Reports · doi:10.1016/j.jorep.2025.100582
Chang, C.-C., Chen, C.-A., Ho, C.-I., Tsai, P., & Wang, T. (2025) · Journal of Asian Pacific Society of Cardiology · doi:10.15420/japsc.2024.24
MacQuarrie, A., Hunter, J. R., Steele, J., Chandramouli, S., Stainer, M. J., Rengers, A., & Wickham, J. B. (2025) · Journal of Healthcare Simulation · doi:10.54531/itnx9528
Vision-based multimodal energy expenditure estimation for aerobic exercise in adults
Jin, L., Zhang, S., Shi, M., Yu, L., Wang, M., Song, M., & Xu, W. (2025) · Frontiers in Physiology · doi:10.3389/fphys.2025.1666616
Burnett, R. A., Matheson, D. J., Kapron, C. R., Blackburn, B. E., Gililland, J. M., Anderson, L. A., Pelt, C. E., Peters, C. L., & Archibeck, M. J. (2025) · The Journal of Arthroplasty · doi:10.1016/j.arth.2025.11.003
Bridging Spirit and Science: Physiological and Spiritual Effects of Wîwîp’son Healing Swing SessionsPreprint
Auger, D., Almond, A., Wright, R. D., Breuer, J., Fletcher, F., & Jones, K. E. (2025) · Research Square · doi:10.21203/rs.3.rs-8399311/v1
Kim, J., Kim, S., & Lee, Y. (2026) · The Korean Society of Costume · doi:10.7233/jksc.2026.76.1.137
Fang, Y., Zhang, W., Zhao, W., Dong, P., & Wan, F. (2026) · Environmental Pollution · doi:10.1016/j.envpol.2026.128138
de Matos, D. G., de Santana, J. L., Aidar, F. J., Cornish, S. M., Giesbrecht, G. G., Nunes-Silva, A., Raj, S. R., Romero‐Ortuño, R., Duhamel, T. A., & Villar, R. (2026) · American Journal of Physiology-Regulatory, Integrative and Comparative Physiology · doi:10.1152/ajpregu.00019.2026
Lee, R. H. Y., Vukovic, S., Lucci, V.-E. M., Lando, J. T., & Claydon, V. E. (2026) · Autonomic Neuroscience · doi:10.1016/j.autneu.2026.103464
Zhao, X., Li, Y., Zhang, L., Wang, J., Jialin, A., An, Q., Fu, Y., Yao, C., & Deng, W. (2026) · JMIR Formative Research · doi:10.2196/89485
Tafazzoli, M., Haq, I., Naeijian, F., Goodarzi, M., & Kamari, M. (2026) · Sustainability · doi:10.3390/su18168359
Metadata
- Authors
- Villar, R., Beltrame, T., & Hughson, R. L.
- Affiliations
- Ministry of Education (BR)
- Conselho Nacional de Desenvolvimento Científico e Tecnológico (BR)
- University of Waterloo (CA)
- Venue
- Applied Physiology Nutrition and Metabolism
- Publisher
- Canadian Science Publishing
- Published
- 2015-10
- Volume
- 40
- Issue
- 10
- Pages
- 1019-1024
- ISSN
- 1715-5312 (ISSN-L)
- 1715-5320
- OpenAlex
- W1845533652
- Cited by
- 178
- References
- 20
- Citations by year
- 2026: 7 · 2025: 23 · 2024: 14 · 2023: 19 · 2022: 23 · 2021: 17 · 2020: 25 · 2019: 17 · 2018: 12 · 2017: 14 · 2016: 6 · 2015: 1
- FWCI
- 5.46
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Applied Physiology, Nutrition, and Metabolism (publishedVersion)
- PubMed (publishedVersion)
- Funders
- Accelerated Innovation Research Initiative Turning Top Science and Ideas into High-Impact Values
- Topics
- Physical Sciences › Engineering › Biomedical Engineering › Non-Invasive Vital Sign Monitoring
- Health Sciences › Medicine › Physiology (medical) › Cardiovascular and exercise physiology
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Context-Aware Activity Recognition Systems
- Keywords
- heart rate monitoring, respiratory rate, tidal volume, minute ventilation, device validation, treadmill walking, posture, exercise intensity, ventilatory threshold, wearable sensors
- MeSH terms
- Adult, Clothing, Equipment Design, Female, Heart Rate, Humans, Male, Posture, Reference Values, Tidal Volume, Reproducibility of Results, Walking, Monitoring, Ambulatory, Respiratory Rate, Accelerometry
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
