Machine Learning and AI Technologies for Smart Wearables

A random forest guided tour

Biau, G., & Scornet, E. (2016) · Test · doi:10.1007/s11749-016-0481-7 · Cited by 4,149 · see citing works

LSTM-CNN Architecture for Human Activity Recognition

Xia, K., Huang, J., & Wang, H. (2020) · IEEE Access · doi:10.1109/access.2020.2982225 · Cited by 851 · see citing works

Recent advances in wearable sensors for animal health management

Neethirajan, S. R. (2016) · Sensing and Bio-Sensing Research · doi:10.1016/j.sbsr.2016.11.004 · Cited by 539 · see citing works

Human Activity Recognition With Smartphone and Wearable Sensors Using Deep Learning Techniques: A Review

Ramanujam, E., Perumal, T., & Padmavathi, S. (2021) · IEEE Sensors Journal · doi:10.1109/jsen.2021.3069927 · Cited by 455 · see citing works

A deep learning approach to on-node sensor data analytics for mobile or wearable devices

Ravi, D., Wong, C., Lo, B., & Yang, G.-Z. (2017) · IEEE Journal of Biomedical and Health Informatics · doi:10.1109/jbhi.2016.2633287 · Cited by 439 · see citing works

An intelligent healthcare monitoring framework using wearable sensors and social networking data

Ali, F., El-Sappagh, S., Islam, S. M. R., Ali, A., Attique, M., Imran, M., & Kwak, K.-S. (2021) · Future Generation Computer Systems · doi:10.1016/j.future.2020.07.047 · Cited by 355 · see citing works

A High Reliability Wearable Device for Elderly Fall Detection

Pierleoni, P., Belli, A., Palma, L., et al. (2015) · IEEE Sensors Journal · doi:10.1109/jsen.2015.2423562 · Cited by 279 · see citing works

Recent Advances in Multiresponsive Flexible Sensors towards E‐skin: A Delicate Design for Versatile Sensing

Li, W., Ke, K., Jia, J. F., Pu, J., Zhao, X., Bao, R., Liu, Z., Bai, L., Zhang, K., Yang, M., et al. (2021) · Small · doi:10.1002/smll.202103734 · Cited by 255 · see citing works

Sensor Data Acquisition and Multimodal Sensor Fusion for Human Activity Recognition Using Deep Learning

Chung, S., Lim, J., Noh, K. J., Kim, G., & Jeong, H. (2019) · Sensors · doi:10.3390/s19071716 · Cited by 215 · see citing works

Remote Patient Monitoring Using Mobile Health for Total Knee Arthroplasty: Validation of a Wearable and Machine Learning–Based Surveillance Platform

Ramkumar, P. N., Haeberle, H. S., Ramanathan, D., Cantrell, W. A., Navarro, S. M., Mont, M. A., Bloomfield, M. R., & Patterson, B. M. (2019) · The Journal of Arthroplasty · doi:10.1016/j.arth.2019.05.021 · Cited by 209 · see citing works

A Movement Decomposition and Machine Learning-Based Fall Detection System Using Wrist Wearable Device

de Quadros, T., Lazzaretti, A. E., & Schneider, F. K. (2018) · IEEE Sensors Journal · doi:10.1109/jsen.2018.2829815 · Cited by 179 · see citing works

A deep learning approach to monitoring and detecting atrial fibrillation using wearable technology

Shashikumar, S. P., Shah, A. J., Qiao, L., Clifford, G. D., & Nemati, S. (2017) · IEEE-EMBS International Conference on Biomedical and Health Informatics (BHI ...) · doi:10.1109/bhi.2017.7897225 · Cited by 167 · see citing works

Sustainable smart city IoT applications: Heat and electricity management & Eco-conscious cruise control for public transportation

Kyriazis, D., Varvarigou, T., Rossi, A., White, D., & Cooper, J. (2013) · 2013 IEEE 14th International Symposium on "A World of Wireless, Mobile and Multimedia Networks" (WoWMoM) · doi:10.1109/wowmom.2013.6583500 · Cited by 147 · see citing works

Deep learning-based smart task assistance in wearable augmented reality

Park, K.-B., Kim, M., Choi, S. H., & Lee, J. Y. (2019) · Robotics and Computer-Integrated Manufacturing · doi:10.1016/j.rcim.2019.101887 · Cited by 139 · see citing works

A Health Decision Support System for Disease Diagnosis Based on Wearable Medical Sensors and Machine Learning Ensembles

Yin, H., & Jha, N. K. (2017) · IEEE Transactions on Multi-Scale Computing Systems · doi:10.1109/tmscs.2017.2710194 · Cited by 131 · see citing works

Sleep devices: wearables and nearables, informational and interventional, consumer and clinical

Bianchi, M. T. (2017) · Metabolism · doi:10.1016/j.metabol.2017.10.008 · Cited by 124 · see citing works

Deep learning with wearable based heart rate variability for prediction of mental and general health

Coutts, L. V., Plans, D., Brown, A. W., & Collomosse, J. P. (2020) · Journal of Biomedical Informatics · doi:10.1016/j.jbi.2020.103610 · Cited by 123 · see citing works

Wearable heart rate monitoring intelligent sports bracelet based on Internet of things

Xiao, N., Yu, W. H., & Han, X. (2020) · Measurement · doi:10.1016/j.measurement.2020.108102 · Cited by 122 · see citing works

EnsemConvNet: a deep learning approach for human activity recognition using smartphone sensors for healthcare applications

Mukherjee, D., Mondal, R., Singh, P. K., Sarkar, R., & Bhattacharjee, D. (2020) · Multimedia Tools and Applications · doi:10.1007/s11042-020-09537-7 · Cited by 113 · see citing works

Identification of Suitable Biomarkers for Stress and Emotion Detection for Future Personal Affective Wearable Sensors

Zamkah, A., Hui, T., Andrews, S., Dey, N., Shi, F., & Sherratt, R. S. (2020) · Biosensors · doi:10.3390/bios10040040 · Cited by 110 · see citing works

Machine learning driven personal comfort prediction by wearable sensing of pulse rate and skin temperature

Chaudhuri, T., Soh, Y. C., Li, H., et al. (2019) · Building and Environment · doi:10.1016/j.buildenv.2019.106615 · Cited by 107 · see citing works

Application Specific Internet of Things (ASIoTs): Taxonomy, Applications, Use Case and Future Directions

Ang, L.-M., & Seng, J. K. P. (2019) · IEEE Access · doi:10.1109/access.2019.2907793 · Cited by 96 · see citing works

Optimized unsupervised deep learning assisted reconstructed coder in the on-nodule wearable sensor for human activity recognition

Janarthanan, R., Doss, S., & Baskar, S. (2020) · Measurement · doi:10.1016/j.measurement.2020.108050 · Cited by 91 · see citing works

Sleep stage classification based on multi-level feature learning and recurrent neural networks via wearable device

Zhang, X., Kou, W., Chang, E., Gao, H., Fan, Y., & Xu, Y. L. (2018) · Computers in Biology and Medicine · doi:10.1016/j.compbiomed.2018.10.010 · Cited by 86 · see citing works

Fall detection system using accelerometer and gyroscope based on smartphone

Rakhman, A. Z., Nugroho, L. E., Widyawan, W., et al. (2014) · doi:10.1109/icitacee.2014.7065722 · Cited by 85 · see citing works

Intelligent positive computing with mobile, wearable, and IoT devices: Literature review and research directions

Lee, U., Han, K., Cho, H., Chung, K., Hong, H., Lee, S.-J., Noh, Y., Park, S., & Carroll, J. M. (2018) · Ad Hoc Networks · doi:10.1016/j.adhoc.2018.08.021 · Cited by 85 · see citing works

Discriminating progressive supranuclear palsy from Parkinson's disease using wearable technology and machine learning

Vos, M. D., Prince, J., Buchanan, T. J., FitzGerald, J. J., & Antoniades, C. A. (2020) · Gait & Posture · doi:10.1016/j.gaitpost.2020.02.007 · Cited by 84 · see citing works

Killer heuristic optimized convolution neural network-based fall detection with wearable IoT sensor devices

Alarifi, A., & Alwadain, A. S. (2020) · Measurement · doi:10.1016/j.measurement.2020.108258 · Cited by 84 · see citing works

Wearables and Deep Learning Classify Fall Risk From Gait in Multiple Sclerosis

Meyer, B. M., Tulipani, L. J., Gurchiek, R. D., Allen, D. A., Adamowicz, L., Larie, D., Solomon, A. J., Cheney, N., & McGinnis, R. S. (2020) · IEEE Journal of Biomedical and Health Informatics · doi:10.1109/jbhi.2020.3025049 · Cited by 84 · see citing works

Lower body kinematics estimation from wearable sensors for walking and running: A deep learning approach

Hernandez, V., Dadkhah, D., Babakeshizadeh, V., & Kulić, D. (2020) · Gait & Posture · doi:10.1016/j.gaitpost.2020.10.026 · Cited by 84 · see citing works

Enhancing perception for the visually impaired with deep learning techniques and low-cost wearable sensors

Bauer, Z., Dominguez, A., Cruz, E., Gomez‐Donoso, F., Orts‐Escolano, S., & Cazorla, M. (2019) · Pattern Recognition Letters · doi:10.1016/j.patrec.2019.03.008 · Cited by 78 · see citing works

Socio-technical barriers affecting large-scale deployment of AI-enabled wearable medical devices among the ageing population in China

Xing, F., Peng, G., Zhang, B., Li, S., & Liang, X. (2021) · Technological Forecasting and Social Change · doi:10.1016/j.techfore.2021.120609 · Cited by 73 · see citing works

Deep learning paired with wearable passive sensing data predicts deterioration in anxiety disorder symptoms across 17–18 years

Jacobson, N. C., Lekkas, D., Huang, R., & Thomas, N. (2020) · Journal of Affective Disorders · doi:10.1016/j.jad.2020.12.086 · Cited by 70 · see citing works

Wearable sensor system for wireless state-of-health determination in cattle

Nagl, L., Schmitz, R., Warren, S., et al. (2004) · doi:10.1109/iembs.2003.1280774 · Cited by 68 · see citing works

A wearable-based posture recognition system with AI-assisted approach for healthcare IoT

Hong, Z., Hong, M., Wang, N., et al. (2021) · Future Generation Computer Systems · doi:10.1016/j.future.2021.08.030 · Cited by 68 · see citing works

Wearable Sport Activity Classification Based on Deep Convolutional Neural Network

Hsu, Y., Chang, H.-C., & Chiu, Y.-J. (2019) · IEEE Access · doi:10.1109/access.2019.2955545 · Cited by 65 · see citing works

Smart Wearables for the Detection of Occupational Physical Fatigue: A Literature Review

Moshawrab, M., Adda, M., Bouzouane, A., Ibrahim, H., & Raad, A. (2022) · Sensors · doi:10.3390/s22197472 · Cited by 62 · see citing works

A Novel Multi-Stage Training Approach for Human Activity Recognition From Multimodal Wearable Sensor Data Using Deep Neural Network

Mahmud, T., Sazzad Sayyed, A. Q. M., Fattah, S. A., & Kung, S.-Y. (2021) · IEEE Sensors Journal · doi:10.1109/jsen.2020.3015781 · Cited by 58 · see citing works

Emotions Detection on an Ambient Intelligent System Using Wearable Devices

Costa, Â., Rincón, J., Carrascosa, C., Julián, V., & Novais, P. (2019) · Workshop on Affective Computing and Context Awareness in Ambient Intelligence · doi:10.1016/j.future.2018.03.038 · Cited by 56 · see citing works

A smartwatch-based medication adherence system

Kalantarian, H., Alshurafa, N. I., Nemati, E., Le, T. D., & Sarrafzadeh, M. (2015) · Wearable and Implantable Body Sensor Networks · doi:10.1109/bsn.2015.7299348 · Cited by 53 · see citing works

A Scalable Smartwatch-Based Medication Intake Detection System Using Distributed Machine Learning

Fozoonmayeh, D., Le, H. V., Wittfoth, E., Geng, C., Ha, N., Wang, J., Vasilenko, M., Ahn, Y., & Woodbridge, D. M.-K. (2020) · Journal of Medical Systems · doi:10.1007/s10916-019-1518-8 · Cited by 51 · see citing works

Design of a Wearable Wireless Multi-Sensor Monitoring System and Application for Activity Recognition Using Deep Learning

Ascioglu, G., & Şenol, Y. (2020) · IEEE Access · doi:10.1109/access.2020.3024003 · Cited by 50 · see citing works

Embedding Recurrent Neural Networks in Wearable Systems for Real-Time Fall Detection

Torti, E., Fontanella, A., Musci, M., Blago, N., Pau, D. P., Leporati, F., & Piastra, M. (2019) · Microprocessors and Microsystems · doi:10.1016/j.micpro.2019.102895 · Cited by 47 · see citing works

Wearables-based multi-task gait and activity segmentation using recurrent neural networks

Martindale, C. F., Christlein, V., Klumpp, P., & Eskofier, B. M. (2020) · Neurocomputing · doi:10.1016/j.neucom.2020.08.079 · Cited by 44 · see citing works

Wearable Devices, Smartphones, and Interpretable Artificial Intelligence in Combating COVID-19

Hijazi, H., Talib, M. W. A., Hasasneh, A., Nassif, A. B., Ahmed, N., & Nasir, Q. (2021) · Sensors · doi:10.3390/s21248424 · Cited by 42 · see citing works

A multilayer interval type-2 fuzzy extreme learning machine for the recognition of walking activities and gait events using wearable sensors

Rubio-Solis, A., Panoutsos, G., Beltran-Perez, C., & Martinez-Hernandez, U. (2020) · Neurocomputing · doi:10.1016/j.neucom.2019.11.105 · Cited by 39 · see citing works

A Novel Machine Learning Based Wearable Belt For Fall Detection

Desai, K., Mane, P., Dsilva, M., Zare, A., Shingala, P., & Ambawade, D. D. (2020) · IEEE International Conference on Computing, Power and Communication Technologies (IC2PCT) · doi:10.1109/gucon48875.2020.9231114 · Cited by 37 · see citing works

A Comparison of Machine Learning Algorithms for Fall Detection using Wearable Sensors

Zurbuchen, N., Bruegger, P., & Wilde, A. (2020) · International Conference on Artificial Intelligence in Information and Communication (ICAIIC) · doi:10.1109/icaiic48513.2020.9065205 · Cited by 34 · see citing works

Deep brain simulation wearable IoT sensor device based Parkinson brain disorder detection using heuristic tubu optimized sequence modular neural network

AlZubi, A. A., Alarifi, A., & Al‐Maitah, M. (2020) · Measurement · doi:10.1016/j.measurement.2020.107887 · Cited by 34 · see citing works

Big Feature Data Analytics: Split and Combine Linear Discriminant Analysis (SC-LDA) for Integration Towards Decision Making Analytics

Seng, J. K. P., & Ang, K. L.-M. (2017) · IEEE Access · doi:10.1109/access.2017.2726543 · Cited by 33 · see citing works

Stereotypical Motor Movement Detection in Dynamic Feature Space

Rad, N. M., Kia, S. M., Zarbo, C., Jurman, G., Venuti, P., & Furlanello, C. (2016) · IEEE ... International Conference on Data Mining workshops · doi:10.1109/icdmw.2016.0076 · Cited by 29 · see citing works

Wearable and autonomous computing for future smart cities: Open challenges

Balsamo, D., Merrett, G. V., Zaghari, B., Wei, Y., Ramchurn, S. D., Stein, S., Weddell, A. S., & Beeby, S. (2017) · International Conference on Software, Telecommunications and Computer Networks (SoftCOM) · doi:10.23919/softcom.2017.8115596 · Cited by 24 · see citing works

Intelligent wearable rehabilitation robot control system based on mobile communication network

Gao, F., Wang, L., & Lin, T. (2020) · Computer Communications · doi:10.1016/j.comcom.2020.01.054 · Cited by 24 · see citing works

A closed-loop deep learning architecture for robust activity recognition using wearable sensors

Saeedi, R., Norgaard, S., & Gebremedhin, A. H. (2017) · IEEE International Conference on Big Data (BigData) · doi:10.1109/bigdata.2017.8257960 · Cited by 20 · see citing works

A CNN Based Human Bowel Sound Segment Recognition Algorithm with Reduced Computation Complexity for Wearable Healthcare System

Zhao, K., Jiang, H., Yuan, T., et al. (2020) · IEEE International Symposium on Circuits and Systems proceedings · doi:10.1109/iscas45731.2020.9180432 · Cited by 20 · see citing works

Enabling Real-Time Quality Inspection in Smart Manufacturing Through Wearable Smart Devices and Deep Learning

Sarivan, I.-M., Greiner, J. N., Álvarez, D., et al. (2020) · Procedia Manufacturing · doi:10.1016/j.promfg.2020.10.053 · Cited by 20 · see citing works

A Real-time intelligent shoe system for fall detection

Tao, Y., Qian, H., Chen, M., et al. (2011) · IEEE International Conference on Robotics and Biomimetics (ROBIO) · doi:10.1109/robio.2011.6181633 · Cited by 19 · see citing works

A Deep Learning Based End-to-End Locomotion Mode Detection Method for Lower Limb Wearable Robot Control

Lu, Z., Narayan, A., & Yu, H. (2020) · IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) · doi:10.1109/iros45743.2020.9341183 · Cited by 19 · see citing works

Printed, wearable e-skin force sensor array

Sapra, S., Chakraborthy, A., Nuthalapati, S., Nag, A., Inglis, D. W., Mukhopadhyay, S. C., & Altinsoy, M. E. (2022) · Measurement · doi:10.1016/j.measurement.2022.112348 · Cited by 18 · see citing works

1D-CNN-based BCI system for detecting Emotional states using a Wireless and Wearable 8-channel Custom-designed EEG Headset

Mai, N.-D., Long, N. M. H., & Chung, W. (2021) · IEEE International Conference on Flexible and Printable Sensors and Systems (FLEPS) · doi:10.1109/fleps51544.2021.9469818 · Cited by 17 · see citing works

Combining Symbolic Reasoning and Deep Learning for Human Activity Recognition

Rueda, F. M., Lüdtke, S., Schröder, M., Yordanova, K., Kirste, T., & Fink, G. A. (2019) · IEEE International Conference on Pervasive Computing and Communications Workshops (PerCom Workshops) · doi:10.1109/percomw.2019.8730792 · Cited by 16 · see citing works

A Deep Learning Based Wearable Healthcare Iot Device for AI-Enabled Hearing Assistance Automation

Young, F., Zhang, L., Jiang, R., Liu, H., & Wall, C. (2020) · International Conference on Machine Learning and Cybernetics · doi:10.1109/icmlc51923.2020.9469537 · Cited by 16 · see citing works

Closed-loop Position Control of a Pediatric Soft Robotic Wearable Device for Upper Extremity Assistance

Mucchiani, C., Liu, Z., Sahin, I., Dube, J., Vu, L., Kokkoni, E., & Karydis, K. (2022) · IEEE RO-MAN · doi:10.1109/ro-man53752.2022.9900650 · Cited by 15 · see citing works

A Discreet Wearable Long-Range Emergency System Based on Embedded Machine Learning

Orfanidis, C., Hassen, R. B. H., Kwiek, A., Fafoutis, X., & Jacobsson, M. (2021) · 2021 IEEE International Conference on Pervasive Computing and Communications Workshops and other Affiliated Events (PerCom Workshops) · doi:10.1109/percomworkshops51409.2021.9430981 · Cited by 14 · see citing works

A Binarized CNN-Based Bowel Sound Recognition Algorithm With Time-Domain Histogram Features for Wearable Healthcare Systems

Zhao, K., Feng, S., Jiang, H., et al. (2021) · IEEE Transactions on Circuits & Systems II Express Briefs · doi:10.1109/tcsii.2021.3097069 · Cited by 12 · see citing works

CNN-based Speed Detection Algorithm for Walking and Running using Wrist-worn Wearable Sensors

Seethi, V. D. R., & Bharti, P. (2020) · IEEE International Conference on Smart Computing · doi:10.1109/smartcomp50058.2020.00064 · Cited by 10 · see citing works

A Machine Learning-Based Countermovement Performance Measurement Method Using a Wearable IMU

Chiang, Y.-Y., Shih, W.-Y., Chen, W.-H., Huang, J., & Shiang, T.-Y. (2020) · International Conference on Pervasive Artificial Intelligence (ICPAI) · doi:10.1109/icpai51961.2020.00022 · Cited by 6 · see citing works

Challenges in Smart Health Applications Using Wearable Medical Internet-of-Things—A Review

Schnell, B., Moder, P., Ehm, H., et al. (2021) · Lecture notes in networks and systems · doi:10.1007/978-981-16-1781-2_27 · Cited by 6 · see citing works

Sleep Stage Classification Based on Multi-level Feature Learning and Recurrent Neural Networks via Wearable DevicePreprint

Zhang, X., Kou, W., Chang, E., et al. (2017) · arXiv (Cornell University) · doi:10.48550/arxiv.1711.00629 · Cited by 1 · see citing works

The emergence of AI-based wearable sensors for digital health technology: a review

Shajari, S., Kuruvinashetti, K., Komeili, A., & Sundararaj, U. (2023) · Sensors · doi:10.3390/s23239498 · Cited by 535 · see citing works

Dataset of fitness trackers and smartwatches to measuring physical activity in research

Henriksen, A., Woldaregay, A. Z., Mužný, M., Hartvigsen, G., Hopstock, L. A., & Grimsgaard, S. (2022) · BMC Research Notes · doi:10.1186/s13104-022-06146-5 · Cited by 5 · see citing works

Smartwatch as an Assistive Technology

Vuković, M., Car, Ž., Pavliša, J. I., et al. (2017) · International Journal of E-Health and Medical Communications · doi:10.4018/ijehmc.2018010102 · Cited by 6 · see citing works

A Survey of the Development of Wearable Devices

Zhou, Q., Fang, B., Shan, J., Sun, F., & Guo, D. (2020) · International Conference on Advanced Robotics and Mechatronics (ICARM) · doi:10.1109/icarm49381.2020.9195351 · Cited by 19 · see citing works

The Promise and Perils of Wearable Technologies

Gammack, J. G., & Marrington, A. (2016) · Advances in information security, privacy, and ethics book series · doi:10.4018/978-1-5225-1016-1.ch001 · Cited by 1 · see citing works

The Promise and Perils of Wearable Technologies

Gammack, J. G., & Marrington, A. (2018) · IGI Global eBooks · doi:10.4018/978-1-5225-5484-4.ch004 · Cited by 1 · see citing works