Artificial intelligence-powered electronic skin

From local explanations to global understanding with explainable AI for trees

Lundberg, S. M., Erion, G., Chen, H., DeGrave, A., Prutkin, J. M., Nair, B., Katz, R., Himmelfarb, J., Bansal, N., & Lee, S.-I. (2020) · Nature Machine Intelligence · doi:10.1038/s42256-019-0138-9 · Cited by 10,551

Fully integrated wearable sensor arrays for multiplexed in situ perspiration analysis

Gao, W., Emaminejad, S., Nyein, H. Y. Y., Challa, S., Chen, K., Peck, A., Fahad, H. M., Ota, H., Shiraki, H., Kiriya, D., et al. (2016) · Nature · doi:10.1038/nature16521 · Cited by 5,087 · cited 3×

Epidermal Electronics

Kim, D.-H., Lu, N., Ma, R., Kim, Y.-S., Kim, R.-H., Wang, S., Wu, J., Won, S. M., Tao, H., Islam, A., et al. (2011) · Science · doi:10.1126/science.1206157 · Cited by 4,836

A stretchable carbon nanotube strain sensor for human-motion detection

Yamada, T., Hayamizu, Y., Yamamoto, Y., Yomogida, Y., Izadi-Najafabadi, A., Futaba, D. N., & Hata, K. (2011) · Nature Nanotechnology · doi:10.1038/nnano.2011.36 · Cited by 3,247

Cardiologist-level arrhythmia detection and classification in ambulatory electrocardiograms using a deep neural network

Hannun, A. Y., Rajpurkar, P., Haghpanahi, M., Tison, G. H., Bourn, C., Turakhia, M. P., & Ng, A. Y. (2019) · Nature Medicine · doi:10.1038/s41591-018-0268-3 · Cited by 3,148

Artificial intelligence in healthcare

Yu, K.-H., Beam, A. L., & Kohane, I. S. (2018) · Nature Biomedical Engineering · doi:10.1038/s41551-018-0305-z · Cited by 2,817

25th Anniversary Article: The Evolution of Electronic Skin (E‐Skin): A Brief History, Design Considerations, and Recent Progress

Hammock, M. L., Chortos, A., Tee, B. C. ‐., Tok, J. B. ‐., & Bao, Z. (2013) · Advanced Materials · doi:10.1002/adma.201302240 · Cited by 2,396

Skin electronics from scalable fabrication of an intrinsically stretchable transistor array

Wang, S., Xu, J., Wang, W., Wang, G. N., Rastak, R., Molina‐Lopez, F., Chung, J. W., Niu, S., Feig, V. R., Lopez, J., et al. (2018) · Nature · doi:10.1038/nature25494 · Cited by 2,216

Benefits, Limits, and Risks of GPT-4 as an AI Chatbot for Medicine

Lee, P., Bubeck, S., & Petro, J. (2023) · New England Journal of Medicine · doi:10.1056/nejmsr2214184 · Cited by 1,738

Dry double-sided tape for adhesion of wet tissues and devices

Yuk, H., Varela, C. E., Nabzdyk, C. S., Mao, X., Padera, R. F., Roche, E. T., & Zhao, X. (2019) · Nature · doi:10.1038/s41586-019-1710-5 · Cited by 1,534

Big data and machine learning algorithms for health-care delivery

Ngiam, K. Y., & Khor, I. W. (2019) · The Lancet Oncology · doi:10.1016/s1470-2045(19)30149-4 · Cited by 1,424

Screening for cardiac contractile dysfunction using an artificial intelligence–enabled electrocardiogram

Attia, Z. I., Kapa, S., Lopez-Jimenez, F., McKie, P. M., Ladewig, D. J., Satam, G., Pellikka, P. A., Enriquez-Sarano, M., Noseworthy, P. A., Munger, T. M., et al. (2019) · Nature Medicine · doi:10.1038/s41591-018-0240-2 · Cited by 1,389

Multimodal biomedical AI

Acosta, J. N., Falcone, G. J., Rajpurkar, P., & Topol, E. J. (2022) · Nature Medicine · doi:10.1038/s41591-022-01981-2 · Cited by 1,365

End-to-end design of wearable sensors

Ates, H. C., Nguyen, P. Q., Gonzalez-Macia, L., Morales-Narváez, E., Güder, F., Collins, J. J., & Dincer, C. (2022) · Nature Reviews Materials · doi:10.1038/s41578-022-00460-x · Cited by 1,306

A laser-engraved wearable sensor for sensitive detection of uric acid and tyrosine in sweat

Yang, Y., Song, Y., Bo, X., Min, J., Pak, O. S., Zhu, L., Wang, M., Tu, J., Kogan, A., Zhang, H., et al. (2020) · Nature Biotechnology · doi:10.1038/s41587-019-0321-x · Cited by 1,270

Artificial Intelligence and Machine Learning in Clinical Medicine, 2023

Haug, C. J., & Drazen, J. M. (2023) · New England Journal of Medicine · doi:10.1056/nejmra2302038 · Cited by 1,215

Soft Microfluidic Assemblies of Sensors, Circuits, and Radios for the Skin

Xu, S., Zhang, Y., Jia, L., Mathewson, K. E., Jang, K.-I., Kim, J., Fu, H., Huang, X., Chava, P., Wang, R., et al. (2014) · Science · doi:10.1126/science.1250169 · Cited by 1,199

User-interactive electronic skin for instantaneous pressure visualization

Wang, C., Hwang, D., Yu, Z., Takei, K., Park, J., Chen, T., Ma, B., & Javey, A. (2013) · Nature Materials · doi:10.1038/nmat3711 · Cited by 1,182

Ultrafast machine vision with 2D material neural network image sensors

Mennel, L., Symonowicz, J., Wachter, S., Polyushkin, D. K., Molina‐Mendoza, A. J., & Mueller, T. (2020) · Nature · doi:10.1038/s41586-020-2038-x · Cited by 1,180

Learning the signatures of the human grasp using a scalable tactile glove

Sundaram, S., Kellnhofer, P., Li, Y., Zhu, J.-Y., Torralba, A., & Matusik, W. (2019) · Nature · doi:10.1038/s41586-019-1234-z · Cited by 1,162

Large-area display textiles integrated with functional systems

Shi, X., Zuo, Y., Zhai, P., Shen, J., Yang, Y., Gao, Z., Liao, M., Wu, J., Wang, J., Xu, X., et al. (2021) · Nature · doi:10.1038/s41586-021-03295-8 · Cited by 1,113

Self-powered ultra-flexible electronics via nano-grating-patterned organic photovoltaics

Park, S., Heo, S. W., Lee, W., Inoue, D., Jiang, Z., Yu, K., Jinno, H., Hashizume, D., Sekino, M., Yokota, T., et al. (2018) · Nature · doi:10.1038/s41586-018-0536-x · Cited by 1,068

Skin-integrated wireless haptic interfaces for virtual and augmented reality

Yu, X., Xie, Z., Yu, Y., Lee, J., Vazquez-Guardado, A., Luan, H., Ruban, J., Ning, X., Akhtar, A., Li, D., et al. (2019) · Nature · doi:10.1038/s41586-019-1687-0 · Cited by 1,025

A wearable electrochemical biosensor for the monitoring of metabolites and nutrients

Wang, M., Yang, Y., Min, J., Song, Y., Tu, J., Mukasa, D., Ye, C., Xu, C., Heflin, N., McCune, J. S., et al. (2022) · Nature Biomedical Engineering · doi:10.1038/s41551-022-00916-z · Cited by 957

A skin-inspired organic digital mechanoreceptor

Tee, B. C.-K., Chortos, A., Berndt, A., Nguyen, A. K., Tom, A., McGuire, A., Lin, Z. C., Tien, K., Bae, W.-G., Wang, H., et al. (2015) · Science · doi:10.1126/science.aaa9306 · Cited by 882

Sign-to-speech translation using machine-learning-assisted stretchable sensor arrays

Zhou, Z., Chen, K. J., Li, X., Zhang, S., Wu, Y., Zhou, Y., Meng, K., Sun, C., He, Q., Fan, W., et al. (2020) · Nature Electronics · doi:10.1038/s41928-020-0428-6 · Cited by 878

Autonomous sweat extraction and analysis applied to cystic fibrosis and glucose monitoring using a fully integrated wearable platform

Emaminejad, S., Gao, W., Wu, E., Davies, Z. A., Yin Yin Nyein, H., Challa, S., Ryan, S. P., Fahad, H. M., Chen, K., Shahpar, Z., et al. (2017) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1701740114 · Cited by 839

A transparent bending-insensitive pressure sensor

Lee, S., Reuveny, A., Reeder, J., Lee, S., Jin, H., Liu, Q., Yokota, T., Sekitani, T., Isoyama, T., Abe, Y., et al. (2016) · Nature Nanotechnology · doi:10.1038/nnano.2015.324 · Cited by 833

Smart textiles for personalized healthcare

Libanori, A., Chen, G., Zhao, X., Zhou, Y., & Chen, J. (2022) · Nature Electronics · doi:10.1038/s41928-022-00723-z · Cited by 784

Skin-Interfaced Wearable Sweat Sensors for Precision Medicine

Min, J., Tu, J., Xu, C., Lukas, H., Shin, S., Yang, Y., Solomon, S. A., Mukasa, D., & Gao, W. F. (2023) · Chemical Reviews · doi:10.1021/acs.chemrev.2c00823 · Cited by 752

All-organic optoelectronic sensor for pulse oximetry

Lochner, C. M., Khan, Y., Pierre, A., & Arias, A. C. (2014) · Nature Communications · doi:10.1038/ncomms6745 · Cited by 734

Machine learning for alloys

Hart, G. L. W., Mueller, T., Toher, C., & Curtarolo, S. (2021) · Nature Reviews Materials · doi:10.1038/s41578-021-00340-w · Cited by 703

A wearable biosensing system with in-sensor adaptive machine learning for hand gesture recognition

Moin, A., Zhou, A., Rahimi, A., Menon, A., Benatti, S., Alexandrov, G., Tamakloe, S., Ting, J., Yamamoto, N. A. D., Khan, Y., et al. (2020) · Nature Electronics · doi:10.1038/s41928-020-00510-8 · Cited by 698

An integrated wearable microneedle array for the continuous monitoring of multiple biomarkers in interstitial fluid

Tehrani, F., Teymourian, H., Wuerstle, B. L., Kavner, J., Patel, R., Furmidge, A., Aghavali, R., Hosseini-Toudeshki, H., Brown, C., Zhang, F., et al. (2022) · Nature Biomedical Engineering · doi:10.1038/s41551-022-00887-1 · Cited by 663

An epidermal patch for the simultaneous monitoring of haemodynamic and metabolic biomarkers

Sempionatto, J. R., Lin, M., Yin, L., De la paz, E., Pei, K., Sonsa-ard, T., de Loyola Silva, A. N., Khorshed, A. A., Zhang, F., Tostado, N., et al. (2021) · Nature Biomedical Engineering · doi:10.1038/s41551-021-00685-1 · Cited by 658

Biofuel-powered soft electronic skin with multiplexed and wireless sensing for human-machine interfaces

Yu, Y., Nassar, J., Xu, C., Min, J., Yang, Y., Dai, A., Doshi, R., Huang, A., Song, Y., Gehlhar, R., et al. (2020) · Science Robotics · doi:10.1126/scirobotics.aaz7946 · Cited by 655

A wearable cardiac ultrasound imager

Hu, H., Huang, H., Li, M., Gao, X., Yin, L., Qi, R., Wu, R. S., Chen, X., Ma, Y., Shi, K., et al. (2023) · Nature · doi:10.1038/s41586-022-05498-z · Cited by 644

The scent of disease: volatile organic compounds of the human body related to disease and disorder

Shirasu, M., & Touhara, K. (2011) · The Journal of Biochemistry · doi:10.1093/jb/mvr090 · Cited by 633

Artificial multimodal receptors based on ion relaxation dynamics

You, I., Mackanic, D. G., Matsuhisa, N., Kang, J., Kwon, J., Beker, L., Mun, J., Suh, W., Kim, T. Y., Tok, J. B.-H., et al. (2020) · Science · doi:10.1126/science.aba5132 · Cited by 632

Bioadhesive ultrasound for long-term continuous imaging of diverse organs

Wang, C., Chen, X., Wang, L., Makihata, M., Liu, H., Zhou, T., & Zhao, X. (2022) · Science · doi:10.1126/science.abo2542 · Cited by 629

Wearable chemical sensors for biomarker discovery in the omics era

Sempionatto, J. R., Lasalde-Ramírez, J. A., Mahato, K., Wang, J., & Gao, W. (2022) · Nature Reviews Chemistry · doi:10.1038/s41570-022-00439-w · Cited by 613

Molecularly selective nanoporous membrane-based wearable organic electrochemical device for noninvasive cortisol sensing

Parlak, O., Keene, S. T., Marais, A., Curto, V. F., & Salleo, A. (2018) · Science Advances · doi:10.1126/sciadv.aar2904 · Cited by 603 · cited 1×

Materials and structural designs of stretchable conductors

Matsuhisa, N., Chen, X., Bao, Z., & Someya, T. (2019) · Chemical Society Reviews · doi:10.1039/c8cs00814k · Cited by 589

Nanoparticle synthesis assisted by machine learning

Tao, H., Wu, T., Aldeghi, M., Wu, T., Aspuru‐Guzik, A., & Kumacheva, E. (2021) · Nature Reviews Materials · doi:10.1038/s41578-021-00337-5 · Cited by 583

Soft magnetic skin for super-resolution tactile sensing with force self-decoupling

Yan, Y., Hu, Z., Yang, Z., Yuan, W., Song, C., Pan, J., & Shen, Y. (2021) · Science Robotics · doi:10.1126/scirobotics.abc8801 · Cited by 576

Gesture recognition using a bioinspired learning architecture that integrates visual data with somatosensory data from stretchable sensors

Wang, M., Yan, Z., Wang, T., Cai, P., Gao, S., Zeng, Y., Wan, C., Wang, H., Pan, L., Yu, J., et al. (2020) · Nature Electronics · doi:10.1038/s41928-020-0422-z · Cited by 575

Wearable materials with embedded synthetic biology sensors for biomolecule detection

Nguyen, P. Q., Soenksen, L. R., Donghia, N. M., Angenent-Mari, N. M., de Puig, H., Huang, A., Lee, R. A., Slomovic, S., Galbersanini, T., Lansberry, G., et al. (2021) · Nature Biotechnology · doi:10.1038/s41587-021-00950-3 · Cited by 573

Pre-symptomatic detection of COVID-19 from smartwatch data

Mishra, T., Wang, M., Metwally, A. A., Bogu, G. K., Brooks, A., Bahmani, A. H., Alavi, A., Celli, A., Higgs, E., Dagan‐Rosenfeld, O., et al. (2020) · Nature Biomedical Engineering · doi:10.1038/s41551-020-00640-6 · Cited by 484

Machine Learning Glove Using Self‐Powered Conductive Superhydrophobic Triboelectric Textile for Gesture Recognition in VR/AR Applications

Wen, F., Sun, Z., He, T., Shi, Q., Zhu, M., Zhang, Z., Li, L., Zhang, T., & Lee, C. (2020) · Advanced Science · doi:10.1002/advs.202000261 · Cited by 482

Investigation of Cortisol Dynamics in Human Sweat Using a Graphene-Based Wireless mHealth System

Torrente-Rodríguez, R. M., Tu, J., Yang, Y., Min, J., Wang, M., Song, Y., Yu, Y., Xu, C., Ye, C., IsHak, W. W., et al. (2020) · Matter · doi:10.1016/j.matt.2020.01.021 · Cited by 479

Skin-inspired quadruple tactile sensors integrated on a robot hand enable object recognition

Li, G., Liu, S., Wang, L., & Zhu, R. (2020) · Science Robotics · doi:10.1126/scirobotics.abc8134 · Cited by 477

Materials Synthesis Insights from Scientific Literature via Text Extraction and Machine Learning

Kim, E., Huang, K., Saunders, A., McCallum, A., Ceder, G., & Olivetti, E. (2017) · Chemistry of Materials · doi:10.1021/acs.chemmater.7b03500 · Cited by 473

Skin-like biosensor system via electrochemical channels for noninvasive blood glucose monitoring

Chen, Y., Lu, S., Zhang, S., Li, Y., Qu, Z., Chen, Y., Lu, B., Wang, X., & Feng, X. (2017) · Science Advances · doi:10.1126/sciadv.1701629 · Cited by 470

Biologically informed deep neural network for prostate cancer discovery

Elmarakeby, H. A., Hwang, J., Arafeh, R., Crowdis, J., Gang, S., Liu, D., AlDubayan, S. H., Salari, K., Kregel, S., Richter, C., et al. (2021) · Nature · doi:10.1038/s41586-021-03922-4 · Cited by 456

Wearable sensor data and self-reported symptoms for COVID-19 detection

Quer, G., Radin, J. M., Gadaleta, M., Baca-Motes, K., Ariniello, L., Ramos, E., Kheterpal, V., Topol, E. J., & Steinhubl, S. R. (2021) · Nature Medicine · doi:10.1038/s41591-020-1123-x · Cited by 447

A tissue-like neurotransmitter sensor for the brain and gut

Li, J., Liu, Y., Yuan, L., Zhang, B., Bishop, E. S., Wang, K., Tang, J., Zheng, Y., Xu, W., Niu, S., et al. (2022) · Nature · doi:10.1038/s41586-022-04615-2 · Cited by 446

Emerging materials intelligence ecosystems propelled by machine learning

Batra, R., Song, L., & Ramprasad, R. (2020) · Nature Reviews Materials · doi:10.1038/s41578-020-00255-y · Cited by 446

Examining individuals’ adoption of healthcare wearable devices: An empirical study from privacy calculus perspective

Li, H., Wu, J., Gao, Y., & Shi, Y. (2016) · International Journal of Medical Informatics · doi:10.1016/j.ijmedinf.2015.12.010 · Cited by 439

An artificial neural tactile sensing system

Chun, S., Kim, J.-S., Yoo, Y., Choi, Y. I., Jung, S. J., Jang, D., Lee, G., Song, K., Nam, K. S., Youn, I., et al. (2021) · Nature Electronics · doi:10.1038/s41928-021-00585-x · Cited by 439

A wearable patch for continuous analysis of thermoregulatory sweat at rest

Nyein, H. Y. Y., Bariya, M., Tran, B., Ahn, C. H., Brown, B. J., Ji, W., Davis, N., & Javey, A. (2021) · Nature Communications · doi:10.1038/s41467-021-22109-z · Cited by 437 · cited 1×

Wearable Electrochemical Sensors for the Monitoring and Screening of Drugs

Teymourian, H., Parrilla, M., Sempionatto, J. R., Montiel, N. F., Barfidokht, A., Echelpoel, R. V., Wael, K. D., & Wang, J. (2020) · ACS Sensors · doi:10.1021/acssensors.0c01318 · Cited by 437

A soft neuroprosthetic hand providing simultaneous myoelectric control and tactile feedback

Gu, G., Zhang, N., Xu, H., Lin, S., Yu, Y., Chai, G., Ge, L., Yang, H., Shao, Q., Sheng, X., et al. (2021) · Nature Biomedical Engineering · doi:10.1038/s41551-021-00767-0 · Cited by 431

Deep learning-enabled triboelectric smart socks for IoT-based gait analysis and VR applications

Zhang, Z., He, T., Zhu, M., Sun, Z., Shi, Q., Zhu, J., Dong, B., Yuce, M. R., & Lee, C. (2020) · npj Flexible Electronics · doi:10.1038/s41528-020-00092-7 · Cited by 425

Large-area MRI-compatible epidermal electronic interfaces for prosthetic control and cognitive monitoring

Tian, L., Zimmerman, B., Akhtar, A., Yu, K. J., Moore, M., Wu, J. C., Larsen, R. J., Lee, J. W., Li, J., Liu, Y., et al. (2019) · Nature Biomedical Engineering · doi:10.1038/s41551-019-0347-x · Cited by 411

Metabolomic profiles predict individual multidisease outcomes

Buergel, T., Steinfeldt, J., Ruyoga, G., Pietzner, M., Bizzarri, D., Vojinovic, D., Upmeier zu Belzen, J., Loock, L., Kittner, P., Christmann, L., et al. (2022) · Nature Medicine · doi:10.1038/s41591-022-01980-3 · Cited by 406

A stretchable wireless wearable bioelectronic system for multiplexed monitoring and combination treatment of infected chronic wounds

Shirzaei Sani, E., Xu, C., Wang, C., Song, Y., Min, J., Tu, J., Solomon, S. A., Li, J., Banks, J. L., Armstrong, D. G., et al. (2023) · Science Advances · doi:10.1126/sciadv.adf7388 · Cited by 405

Learning human–environment interactions using conformal tactile textiles

Luo, Y., Li, Y., Sharma, P., Shou, W., Wu, K., Foshey, M., Li, B., Palacios, T., Torralba, A., & Matusik, W. (2021) · Nature Electronics · doi:10.1038/s41928-021-00558-0 · Cited by 395 · cited 2×

A wireless patch for the monitoring of C-reactive protein in sweat

Tu, J., Min, J., Song, Y., Xu, C., Li, J., Moore, J., Hanson, J., Hu, E., Parimon, T., Wang, T.-Y., et al. (2023) · Nature Biomedical Engineering · doi:10.1038/s41551-023-01059-5 · Cited by 395

Wearable Microsensor Array for Multiplexed Heavy Metal Monitoring of Body Fluids

Gao, W. F., Nyein, H. Y. Y., Shahpar, Z., Fahad, H. M., Chen, K., Emaminejad, S., Gao, Y., Tai, L., Ota, H., Wu, E. G., et al. (2016) · ACS Sensors · doi:10.1021/acssensors.6b00287 · Cited by 393

Ambulatory Cardiovascular Monitoring Via a Machine‐Learning‐Assisted Textile Triboelectric Sensor

Fang, Y., Zou, Y., Xu, J. H., Chen, G., Zhou, Y., Deng, W., Zhao, X., Roustaei, M., Hsiai, T. K., & Chen, J. (2021) · Advanced Materials · doi:10.1002/adma.202104178 · Cited by 387

Monitoring stress with a wrist device using context

Gjoreski, M., Luštrek, M., Gams, M., & Gjoreski, H. (2017) · Journal of Biomedical Informatics · doi:10.1016/j.jbi.2017.08.006 · Cited by 379

All-printed soft human-machine interface for robotic physicochemical sensing

Yu, Y., Li, J., Solomon, S. A., Min, J., Tu, J., Guo, W. H., Xu, C., Song, Y., & Gao, W. F. (2022) · Science Robotics · doi:10.1126/scirobotics.abn0495 · Cited by 379

Current status of clinical breath analysis

Risby, T. H., & Solga, S. F. (2006) · Applied Physics B · doi:10.1007/s00340-006-2280-4 · Cited by 375

Battery-free, wireless sensors for full-body pressure and temperature mapping

Han, S., Kim, J., Won, S. M., Ma, Y., Kang, D., Xie, Z., Lee, K., Chung, H. U., Banks, A. R., Min, S., et al. (2018) · Science Translational Medicine · doi:10.1126/scitranslmed.aan4950 · Cited by 363

Artificial tactile perception smart finger for material identification based on triboelectric sensing

Qu, X., Liu, Z., Tan, P., Wang, C., Liu, Y., Feng, H., Luo, D., Li, Z., & Wang, Z. L. (2022) · Science Advances · doi:10.1126/sciadv.abq2521 · Cited by 363

Stretchable temperature-sensing circuits with strain suppression based on carbon nanotube transistors

Zhu, C., Chortos, A., Wang, Y., Pfattner, R., Lei, T., Hinckley, A. C., Pochorovski, I., Yan, X., To, J. W. F., Oh, J. Y., et al. (2018) · Nature Electronics · doi:10.1038/s41928-018-0041-0 · Cited by 362

Mouthguard biosensor with telemetry system for monitoring of saliva glucose: A novel cavitas sensor

Arakawa, T., Kuroki, Y., Nitta, H., Chouhan, P., Toma, K., Sawada, S.-I., Takeuchi, S., Sekita, T., Akiyoshi, K., Minakuchi, S., et al. (2016) · Biosensors and Bioelectronics · doi:10.1016/j.bios.2015.12.014 · Cited by 356

GCN-RL Circuit Designer: Transferable Transistor Sizing with Graph Neural Networks and Reinforcement Learning

Wang, H., Wang, K., Yang, J., Shen, L., Sun, N., Lee, H.-S., & Han, S. (2020) · ACM/IEEE Design Automation Conference (DAC) · doi:10.1109/dac18072.2020.9218757 · Cited by 343

Personalizing exoskeleton assistance while walking in the real world

Slade, P., Kochenderfer, M. J., Delp, S. L., & Collins, S. H. (2022) · Nature · doi:10.1038/s41586-022-05191-1 · Cited by 339

Electronic skin as wireless human-machine interfaces for robotic VR

Liu, Y., Yiu, C. K., Song, Z. F., Huang, Y., Yao, K., Wong, T., Zhou, J., Zhao, L., Huang, X., Nejad, S. K., et al. (2022) · Science Advances · doi:10.1126/sciadv.abl6700 · Cited by 315

Prospects and Challenges of Volatile Organic Compound Sensors in Human Healthcare

Jalal, A. H., Alam, F., Roychoudhury, S., Umasankar, Y., Pala, N., & Bhansali, S. (2018) · ACS Sensors · doi:10.1021/acssensors.8b00400 · Cited by 315

A Machine Learning-Based Big EEG Data Artifact Detection and Wavelet-Based Removal: An Empirical Approach

Stalin, S., Roy, V., Shukla, P. K., Zaguia, A., Khan, M. M., Shukla, P. K., & Jain, A. (2021) · Mathematical Problems in Engineering · doi:10.1155/2021/2942808 · Cited by 312

Methylxanthine Drug Monitoring with Wearable Sweat Sensors

Tai, L., Gao, W., Chao, M., Bariya, M., Ngo, Q. P., Shahpar, Z., Nyein, H. Y. Y., Park, H., Sun, J., Jung, Y., et al. (2018) · Advanced Materials · doi:10.1002/adma.201707442 · Cited by 310

Artificial intelligence-enabled detection and assessment of Parkinson’s disease using nocturnal breathing signals

Yang, Y., Yuan, Y., Zhang, G., Wang, H., Chen, Y.-C., Liu, Y., Tarolli, C. G., Crepeau, D., Bukartyk, J., Junna, M. R., et al. (2022) · Nature Medicine · doi:10.1038/s41591-022-01932-x · Cited by 296

Portable Food‐Freshness Prediction Platform Based on Colorimetric Barcode Combinatorics and Deep Convolutional Neural Networks

Guo, L., Wang, T., Wu, Z., Wang, J., Wang, M., Cui, Z., Ji, S., Cai, J., Xu, C., & Chen, X. (2020) · Advanced Materials · doi:10.1002/adma.202004805 · Cited by 294

A wireless haptic interface for programmable patterns of touch across large areas of the skin

Jung, Y. H., Yoo, J., Vázquez‐Guardado, A., Kim, J.-H., Kim, J., Luan, H., Park, M., Lim, J., Shin, H., Su, C., et al. (2022) · Nature Electronics · doi:10.1038/s41928-022-00765-3 · Cited by 269

Wearable microneedle-based electrochemical aptamer biosensing for precision dosing of drugs with narrow therapeutic windows

Lin, S., Cheng, X., Zhu, J., Wang, B., Jelínek, D., Zhao, Y., Wu, T., Horrillo, A., Tan, J., Yeung, J., et al. (2022) · Science Advances · doi:10.1126/sciadv.abq4539 · Cited by 267

A soft thumb-sized vision-based sensor with accurate all-round force perception

Sun, H., Kuchenbecker, K. J., & Martius, G. (2022) · Nature Machine Intelligence · doi:10.1038/s42256-021-00439-3 · Cited by 264

Machine learning and computation-enabled intelligent sensor design

Ballard, Z. S., Brown, C., Madni, A. M., & Özcan, A. (2021) · Nature Machine Intelligence · doi:10.1038/s42256-021-00360-9 · Cited by 262

Continuous cuffless monitoring of arterial blood pressure via graphene bioimpedance tattoos

Kireev, D., Sel, K., Ibrahim, B., Kumar, N., Akbari, A., Jafari, R., & Akinwande, D. (2022) · Nature Nanotechnology · doi:10.1038/s41565-022-01145-w · Cited by 249

Integration of novel monitoring devices with machine learning technology for scalable cardiovascular management

Krittanawong, C., Rogers, A. J., Johnson, K. W., Wang, Z., Turakhia, M. P., Halperin, J. L., & Narayan, S. M. (2020) · Nature Reviews Cardiology · doi:10.1038/s41569-020-00445-9 · Cited by 248

Sensitive pressure sensors based on conductive microstructured air-gap gates and two-dimensional semiconductor transistors

Huang, Y.-C., Liu, Y., Ma, C., Cheng, H.-C., He, Q., Wu, H., Wang, C., Lin, C.-Y., Huang, Y., & Duan, X. (2020) · Nature Electronics · doi:10.1038/s41928-019-0356-5 · Cited by 233

Encoding of tactile information in hand via skin-integrated wireless haptic interface

Yao, K., Zhou, J., Huang, Q., Wu, M., Yiu, C. K., Li, J., Huang, X., Li, D., Su, J., Hou, S., et al. (2022) · Nature Machine Intelligence · doi:10.1038/s42256-022-00543-y · Cited by 230

3D-printed epifluidic electronic skin for machine learning–powered multimodal health surveillance

Song, Y., Tay, R. Y., Li, J., Xu, C., Min, J., Sani, E. S., Kim, G., Heng, W., Kim, I. H., & Gao, W. F. (2023) · Science Advances · doi:10.1126/sciadv.adi6492 · Cited by 228

Anthropogenic biases in chemical reaction data hinder exploratory inorganic synthesis

Jia, X., Lynch, A., Huang, Y., Danielson, M., Lang’at, I., Milder, A., Ruby, A. E., Wang, H., Friedler, S. A., Norquist, A. J., et al. (2019) · Nature · doi:10.1038/s41586-019-1540-5 · Cited by 222

Biomimetic and flexible piezoelectric mobile acoustic sensors with multiresonant ultrathin structures for machine learning biometrics

Wang, H. S., Hong, S. K., Han, J. H., Jung, Y.-H., Jeong, H. K., Im, T. H., Jeong, C. K., Lee, B., Kim, G., Yoo, C. D., et al. (2021) · Science Advances · doi:10.1126/sciadv.abe5683 · Cited by 221

Development and Evaluation of an Ambulatory Stress Monitor Based on Wearable Sensors

Choi, J., Ahmed, B., & Gutierrez-Osuna, R. (2012) · IEEE Transactions on Information Technology in Biomedicine · doi:10.1109/titb.2011.2169804 · Cited by 221

Hierarchically resistive skins as specific and multimetric on-throat wearable biosensors

Gong, S. P., Zhang, X., Nguyen, X. A., Shi, Q., Lin, F., Chauhan, S., Ge, Z., & Cheng, W. (2023) · Nature Nanotechnology · doi:10.1038/s41565-023-01383-6 · Cited by 213

Functional mimicry of Ruffini receptors with fibre Bragg gratings and deep neural networks enables a bio-inspired large-area tactile-sensitive skin

Massari, L., Fransvea, G., D’Abbraccio, J., Filosa, M., Terruso, G., Aliperta, A., D’Alesio, G., Zaltieri, M., Schena, E., Palermo, E., et al. (2022) · Nature Machine Intelligence · doi:10.1038/s42256-022-00487-3 · Cited by 203

Near–hysteresis-free soft tactile electronic skins for wearables and reliable machine learning

Yao, H., Yang, W., Cheng, W. M., Tan, Y. J., See, H. H., Li, S., Ali, H. P. A., Lim, B. Z. H., Liu, Z., & Tee, B. C. K. (2020) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2010989117 · Cited by 197

Advances in Artificial Intelligence for Infectious-Disease Surveillance

Brownstein, J. S., Rader, B. M., Astley, C. M., & Tian, H. (2023) · New England Journal of Medicine · doi:10.1056/nejmra2119215 · Cited by 195

Mixed-modality speech recognition and interaction using a wearable artificial throat

Yang, Q., Jin, W., Zhang, Q., Wei, Y., Guo, Z., Li, X., Yang, Y., Luo, Q., Tian, H., & Ren, T. (2023) · Nature Machine Intelligence · doi:10.1038/s42256-023-00616-6 · Cited by 188

A substrate-less nanomesh receptor with meta-learning for rapid hand task recognition

Kim, K. K., Kim, M., Pyun, K. R., Kim, J., Min, J., Koh, S., Root, S. E., Kim, J., Nguyen, B. T., Nishio, Y., et al. (2022) · Nature Electronics · doi:10.1038/s41928-022-00888-7 · Cited by 185

Fully portable and wireless universal brain–machine interfaces enabled by flexible scalp electronics and deep learning algorithm

Mahmood, M., Mzurikwao, D., Kim, Y.-S., Lee, Y., Mishra, S., Herbert, R., Duarte, A., Ang, C. S., & Yeo, W.-H. (2019) · Nature Machine Intelligence · doi:10.1038/s42256-019-0091-7 · Cited by 181 · cited 1×

An ultraflexible organic differential amplifier for recording electrocardiograms

Sugiyama, M., Uemura, T., Kondo, M., AKIYAMA, M., Namba, N., Yoshimoto, S., Noda, Y., Araki, T., & Sekitani, T. (2019) · Nature Electronics · doi:10.1038/s41928-019-0283-5 · Cited by 181

An elastic and reconfigurable synaptic transistor based on a stretchable bilayer semiconductor

Shim, H., Ershad, F., Patel, S. B., Zhang, Y., Wang, B., Chen, Z., Marks, T. J., Facchetti, A. F., & Yu, C. (2022) · Nature Electronics · doi:10.1038/s41928-022-00836-5 · Cited by 180

Wearable Sweat Band for Noninvasive Levodopa Monitoring

Tai, L.-C., Liaw, T. S., Lin, Y., Nyein, H. Y. Y., Bariya, M., Ji, W., Hettick, M., Zhao, C., Zhao, J., Hou, L., et al. (2019) · Nano Letters · doi:10.1021/acs.nanolett.9b02478 · Cited by 177

Accelerated Search and Design of Stretchable Graphene Kirigami Using Machine Learning

Hanakata, P. Z., Cubuk, E. D., Campbell, D. K., & Park, H. S. (2018) · Physical Review Letters · doi:10.1103/physrevlett.121.255304 · Cited by 173

Deep learning-based robust positioning for all-weather autonomous driving

Almalıoğlu, Y., Turan, M., Trigoni, N., & Markham, A. (2022) · Nature Machine Intelligence · doi:10.1038/s42256-022-00520-5 · Cited by 170

Microheater Integrated Nanotube Array Gas Sensor for Parts-Per-Trillion Level Gas Detection and Single Sensor-Based Gas Discrimination

Tang, W., Chen, Z., Song, Z., Wang, C., Wan, Z., Chan, C. L. J., Chen, Z., Ye, W., & Fan, Z. (2022) · ACS Nano · doi:10.1021/acsnano.2c03372 · Cited by 170

A Personalized Acoustic Interface for Wearable Human–Machine Interaction

Lin, Z., Zhang, G., Xiao, X., Au, C., Zhou, Y., Sun, C., Zhou, Z., Yan, R. G., Fan, E., Si, S., et al. (2021) · Advanced Functional Materials · doi:10.1002/adfm.202109430 · Cited by 161

Knowledge-integrated machine learning for materials: lessons from gameplaying and robotics

Hippalgaonkar, K., Li, Q., Wang, X., Fisher, J. S., Kirkpatrick, J., & Buonassisi, T. (2023) · Nature Reviews Materials · doi:10.1038/s41578-022-00513-1 · Cited by 156

Inorganic Materials Synthesis Planning with Literature-Trained Neural Networks

Kim, E., Jensen, Z., van Grootel, A., Huang, K., Staib, M., Mysore, S., Chang, H.-S., Strubell, E., McCallum, A., Jegelka, S., et al. (2020) · Journal of Chemical Information and Modeling · doi:10.1021/acs.jcim.9b00995 · Cited by 151

Deep learning models for electrocardiograms are susceptible to adversarial attack

Han, X., Hu, Y., Foschini, L., Chinitz, L. A., Jankelson, L., & Ranganath, R. (2020) · Nature Medicine · doi:10.1038/s41591-020-0791-x · Cited by 146

A photoacoustic patch for three-dimensional imaging of hemoglobin and core temperature

Gao, X., Chen, X., Hu, H., Wang, X., Yue, W., Mu, J., Lou, Z., Zhang, R., Shi, K., Chen, X., et al. (2022) · Nature Communications · doi:10.1038/s41467-022-35455-3 · Cited by 145

Deep ECGNet: An Optimal Deep Learning Framework for Monitoring Mental Stress Using Ultra Short-Term ECG Signals

Hwang, B., You, J., Vaessen, T., Myin‐Germeys, I., Park, C., & Zhang, B. (2018) · Telemedicine Journal and e-Health · doi:10.1089/tmj.2017.0250 · Cited by 138

Convolutional Neural Network for Drowsiness Detection Using EEG Signals

Chaabene, S., Bouaziz, B., Boudaya, A., Hökelmann, A., Ammar, A., & Chaâri, L. (2021) · Sensors · doi:10.3390/s21051734 · Cited by 135

Soft, miniaturized, wireless olfactory interface for virtual reality

Liu, Y., Yiu, C. K., Zhao, Z., Park, W., Shi, R., Huang, X., Zeng, Y., Wang, K., Wong, T. H., Jia, S., et al. (2023) · Nature Communications · doi:10.1038/s41467-023-37678-4 · Cited by 131

Blood Ketone Bodies and Breath Acetone Analysis and Their Correlations in Type 2 Diabetes Mellitus

Saasa, V., Beukes, M., Lemmer, Y., & Mwakikunga, B. W. (2019) · Diagnostics · doi:10.3390/diagnostics9040224 · Cited by 130

Stretchable colour-sensitive quantum dot nanocomposites for shape-tunable multiplexed phototransistor arrays

Song, J., Kim, J., Yoon, J., Koo, J. H., Jung, H., Kang, K., Sunwoo, S., Yoo, S., Chang, H., Jo, J., et al. (2022) · Nature Nanotechnology · doi:10.1038/s41565-022-01160-x · Cited by 129

Machine learning from wristband sensor data for wearable, noninvasive seizure forecasting

Meisel, C., Atrache, R. E., Jackson, M. C., Schubach, S., Ufongene, C., & Loddenkemper, T. (2020) · Epilepsia · doi:10.1111/epi.16719 · Cited by 123

Personalized machine learning of depressed mood using wearables

Shah, R. V., Grennan, G., Zafar-Khan, M., Alim, F., Dey, S., Ramanathan, D., & Mishra, J. (2021) · Translational Psychiatry · doi:10.1038/s41398-021-01445-0 · Cited by 123

Sweat Testing in Opioid Users with a Sweat Patch

Kintz, P., Tracqui, A., Mangin, P., & Edel, Y. (1996) · Journal of Analytical Toxicology · doi:10.1093/jat/20.6.393 · Cited by 119

A hardwired machine learning processing engine fabricated with submicron metal-oxide thin-film transistors on a flexible substrate

Özer, E., Kufel, J., Myers, J., Biggs, J., Gavin Brown, B., Rana, A., Sou, A., Ramsdale, C. M., & White, S. (2020) · Nature Electronics · doi:10.1038/s41928-020-0437-5 · Cited by 119

Machine Learning-Based Rapid Detection of Volatile Organic Compounds in a Graphene Electronic Nose

Capman, N. S. S., Zhen, X. V., Nelson, J. T., Chaganti, V. R. S. K., Finc, R. C., Lyden, M. J., Williams, T. L., Freking, M., Sherwood, G. J., Bühlmann, P., et al. (2022) · ACS Nano · doi:10.1021/acsnano.2c10240 · Cited by 115

Flexible submental sensor patch with remote monitoring controls for management of oropharyngeal swallowing disorders

Kim, M. K., Kantarcigil, Ç., Kim, B., Baruah, R. K., Maity, S., Park, Y., Kim, K., Lee, S., Malandraki, J. B., Avlani, S., et al. (2019) · Science Advances · doi:10.1126/sciadv.aay3210 · Cited by 112

A Machine‐Learning‐Enhanced Simultaneous and Multimodal Sensor Based on Moist‐Electric Powered Graphene Oxide

Yang, C., Wang, H., Yang, J., Yao, H., He, T., Bai, J., Guang, T., Cheng, H., Yan, J., & Qu, L. (2022) · Advanced Materials · doi:10.1002/adma.202205249 · Cited by 110

Materials and devices for immersive virtual reality

Pyun, K. R., Rogers, J. A., & Ko, S. H. (2022) · Nature Reviews Materials · doi:10.1038/s41578-022-00501-5 · Cited by 110

Active mechanical haptics with high-fidelity perceptions for immersive virtual reality

Zhang, Z., Xu, Z., Emu, L., Wei, P., Chen, S., Zhai, Z., Kong, L., Wang, Y., & Jiang, H. (2023) · Nature Machine Intelligence · doi:10.1038/s42256-023-00671-z · Cited by 100

Touchscreen typing pattern analysis for remote detection of the depressive tendency

Mastoras, R.-E., Iakovakis, D., Hadjidimitriou, S., Charisis, V. S., Kassie, S. A., Alsaadi, T. M., Khandoker, A. H., & Hadjileontiadis, L. J. (2019) · Scientific Reports · doi:10.1038/s41598-019-50002-9 · Cited by 99

Decoding of facial strains via conformable piezoelectric interfaces

Sun, T., Tasnim, F., McIntosh, R. T., Amiri, N., Solav, D., Anbarani, M. T., Sadat, D., Zhang, L., Gu, Y. A., Karami, M. A., et al. (2020) · Nature Biomedical Engineering · doi:10.1038/s41551-020-00612-w · Cited by 99

Automated, multiparametric monitoring of respiratory biomarkers and vital signs in clinical and home settings for COVID-19 patients

Ni, X., Ouyang, W., Jeong, H., Kim, J., Tzavelis, A., Mirzazadeh, A., Wu, C., Lee, J. Y., Keller, M., Mummidisetty, C. K., et al. (2021) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2026610118 · Cited by 98

Machine Learning and Pharmacometrics for Prediction of Pharmacokinetic Data: Differences, Similarities and Challenges Illustrated with Rifampicin

Keutzer, L., You, H., Farnoud, A., Nyberg, J., Wicha, S. G., Maher‐Edwards, G., Vlasakakis, G., Moghaddam, G. K., Svensson, E. M., Menden, M. P., et al. (2022) · Pharmaceutics · doi:10.3390/pharmaceutics14081530 · Cited by 98

Prediction of Core Body Temperature Based on Skin Temperature, Heat Flux, and Heart Rate Under Different Exercise and Clothing Conditions in the Heat in Young Adult Males

Eggenberger, P., MacRae, B. A., Kemp, S., Bürgisser, M., Rossi, R. M., & Annaheim, S. (2018) · Frontiers in Physiology · doi:10.3389/fphys.2018.01780 · Cited by 91

Brain-inspired multimodal hybrid neural network for robot place recognition

Yu, F., Wu, Y., Ma, S., Xu, M., Li, H., Qu, H., Song, C., Wang, T., Zhao, R. J., & Shi, L. (2023) · Science Robotics · doi:10.1126/scirobotics.abm6996 · Cited by 89

Nicotine Monitoring with a Wearable Sweat Band

Tai, L., Ahn, C. H., Nyein, H. Y. Y., Ji, W., Bariya, M., Lin, Y., Li, L., & Javey, A. (2020) · ACS Sensors · doi:10.1021/acssensors.0c00791 · Cited by 87

Machine Learning Models for Human In Vivo Pharmacokinetic Parameters with In-House Validation

Miljković, F. N., Martinsson, A., Obrezanova, O., Williamson, B., Johnson, M. G., Sykes, A. P., Bender, A., & Greene, N. (2021) · Molecular Pharmaceutics · doi:10.1021/acs.molpharmaceut.1c00718 · Cited by 87

Machine-Learning-Aided Self-Powered Assistive Physical Therapy Devices

Xiao, X., Fang, Y., Xiao, X., Xu, J. H., & Chen, J. (2021) · ACS Nano · doi:10.1021/acsnano.1c10676 · Cited by 86

Multimodal sensing and intuitive steering assistance improve navigation and mobility for people with impaired vision

Slade, P., Tambe, A., & Kochenderfer, M. J. (2021) · Science Robotics · doi:10.1126/scirobotics.abg6594 · Cited by 86

Printed, Wireless, Soft Bioelectronics and Deep Learning Algorithm for Smart Human–Machine Interfaces

Kwon, Y., Kim, H., Mahmood, M., Kim, Y., Demolder, C., & Yeo, W. (2020) · ACS Applied Materials & Interfaces · doi:10.1021/acsami.0c14193 · Cited by 82

Diving beetle–like miniaturized plungers with reversible, rapid biofluid capturing for machine learning–based care of skin disease

Baik, S., Lee, J., Jeon, E. J., Park, B., Kim, D. W., Song, J. H., Lee, H. J., Han, S. Y., Cho, S., & Pang, C. (2021) · Science Advances · doi:10.1126/sciadv.abf5695 · Cited by 82

Nonintrusive Monitoring of Mental Fatigue Status Using Epidermal Electronic Systems and Machine-Learning Algorithms

Zeng, Z., Huang, Z., Leng, K., Han, W., Niu, H., Yu, Y., Ling, Q., Liu, J., Wu, Z., & Zang, J. (2020) · ACS Sensors · doi:10.1021/acssensors.9b02451 · Cited by 80

Conformability of flexible sheets on spherical surfaces

Liu, S., He, J., Rao, Y., Dai, Z., Ye, H., Tanir, J. C., Li, Y., & Lu, N. (2023) · Science Advances · doi:10.1126/sciadv.adf2709 · Cited by 73

A Computationally Assisted Approach for Designing Wearable Biosensors toward Non‐Invasive Personalized Molecular Analysis

Mukasa, D., Wang, M., Min, J., Yang, Y., Solomon, S. A., Han, H., Ye, C., & Gao, W. F. (2023) · Advanced Materials · doi:10.1002/adma.202212161 · Cited by 73

Noninvasive Neural Interfacing With Wearable Muscle Sensors: Combining Convolutive Blind Source Separation Methods and Deep Learning Techniques for Neural Decoding

Holobar, A., & Farina, D. (2021) · IEEE Signal Processing Magazine · doi:10.1109/msp.2021.3057051 · Cited by 70

A deep learning-based framework For ECG signal denoising based on stacked cardiac cycle tensor

Rasti-Meymandi, A., & Ghaffari, A. (2021) · Biomedical Signal Processing and Control · doi:10.1016/j.bspc.2021.103275 · Cited by 70

Inverse Design of Inflatable Soft Membranes Through Machine Learning

Forte, A. E., Hanakata, P. Z., Jin, L., Zari, E., Zareei, A., Fernandes, M. C., Sumner, L., Alvarez, J. T., & Bertoldi, K. (2022) · Advanced Functional Materials · doi:10.1002/adfm.202111610 · Cited by 65

Point-of-use sensors and machine learning enable low-cost determination of soil nitrogen

Grell, M., Barandun, G., Asfour, T., Kasimatis, M., Collins, A., Wang, J., & Güder, F. (2021) · Nature Food · doi:10.1038/s43016-021-00416-4 · Cited by 62

Practical Applications of Deep Learning To Impute Heterogeneous Drug Discovery Data

Irwin, B., Levell, J. R., Whitehead, T. M., Segall, M., & Conduit, G. J. (2020) · Journal of Chemical Information and Modeling · doi:10.1021/acs.jcim.0c00443 · Cited by 60

Machine learning-assisted calibration of Hg2+ sensors based on carbon nanotube field-effect transistors

Bian, L., Wang, Z., White, D. L., & Star, A. (2021) · Biosensors and Bioelectronics · doi:10.1016/j.bios.2021.113085 · Cited by 49

High‐Performance Voice Recognition Based on Piezoelectric Polyacrylonitrile Nanofibers

Shao, H., Wang, H., Cao, Y., Ding, X., Fang, J. H., Wang, W., Jin, X., Peng, L., Zhang, D., & Lin, T. (2021) · Advanced Electronic Materials · doi:10.1002/aelm.202100206 · Cited by 49

Fatigue Monitoring in Running Using Flexible Textile Wearable Sensors

Gholami, M., Napier, C., Patiño, A. G., Cuthbert, T. J., & Menon, C. (2020) · Sensors · doi:10.3390/s20195573 · Cited by 40

Advanced machine learning tools to monitor biomarkers of dysphagia: a wearable sensor proof-of-concept study

O’Brien, M. K., Botonis, O. K., Larkin, E., Carpenter, J., Martin-Harris, B., Maronati, R., Lee, K., Cherney, L. R., Hutchison, B., Xu, S., et al. (2021) · Digital Biomarkers · doi:10.1159/000517144 · Cited by 37

Closed-loop network of skin-interfaced wireless devices for quantifying vocal fatigue and providing user feedback

Jeong, H., Yoo, J., Ouyang, W., Greane, A. L. J. X., Wiebe, A. J., Huang, I. A., Lee, Y. J., Lee, J. Y., Kim, J., Ni, X., et al. (2023) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2219394120 · Cited by 32

Driver monitoring and passenger interaction system using wearable device in intelligent vehicle

Ponnan, S., Theivadas, J. R., Hemakumar, V. S., & Einarson, D. (2022) · Computers & Electrical Engineering · doi:10.1016/j.compeleceng.2022.108323 · Cited by 29

Breath odor-based individual authentication by an artificial olfactory sensor system and machine learning

Jirayupat, C., Nagashima, K., Hosomi, T., Takahashi, T., Samransuksamer, B., Hanai, Y., Nakao, A., Nakatani, M., Liu, J., Zhang, G., et al. (2022) · Chemical Communications · doi:10.1039/d1cc06384g · Cited by 28

Machine learning-assisted E-jet printing for manufacturing of organic flexible electronics

Shirsavar, M. A., Taghavimehr, M., Ouedraogo, L. J. G., Javaheripi, M., Hashemi, N. N., Koushanfar, F., & Montazami, R. (2022) · Biosensors and Bioelectronics · doi:10.1016/j.bios.2022.114418 · Cited by 24

Accelerating evaluation of the mobility of ionic liquid-modulated PEDOT flexible electronics using machine learning

Ding, W., Lu, Y., Peng, X., Dong, H., Chi, W., Yuan, X., Sun, Z., & He, H. (2021) · Journal of Materials Chemistry A · doi:10.1039/d1ta08013j · Cited by 14

Reinforcement Learning in Medical Diagnosis: An Overview

Khajuria, R., & Sarwar, A. (2022) · Lecture notes in electrical engineering · doi:10.1007/978-981-16-8248-3_15 · Cited by 6

Wound management materials and technologies from bench to bedside and beyond

Wang, C., Sani, E. S., Shih, C.-D., Lim, C. T., Wang, J., Armstrong, D. G., & Gao, W. F. (2024) · Nature Reviews Materials · doi:10.1038/s41578-024-00693-y · Cited by 448

Diving into Sweat: Advances, Challenges, and Future Directions in Wearable Sweat Sensing

Childs, A., Mayol, B., Lasalde‐Ramírez, J. A., Song, Y., Sempionatto, J. R., & Gao, W. F. (2024) · ACS Nano · doi:10.1021/acsnano.4c10344 · Cited by 241

Designing nanotheranostics with machine learning

Rao, L., Yuan, Y., Shen, X., Yu, G., & Chen, X. S. (2024) · Nature Nanotechnology · doi:10.1038/s41565-024-01753-8 · Cited by 231

Transforming Healthcare: Intelligent Wearable Sensors Empowered by Smart Materials and Artificial Intelligence

Chen, S., Fan, S., Qiao, Z., Wu, Z., Lin, B., Li, Z., Riegler, M. A., Wong, M. Y. H., Opheim, A. I., Korostynska, O., et al. (2025) · Advanced Materials · doi:10.1002/adma.202500412 · Cited by 206

Toward an AI Era: Advances in Electronic Skins

Fu, X., Cheng, W., Wan, G., Yang, Z., & Tee, B. C. K. (2024) · Chemical Reviews · doi:10.1021/acs.chemrev.4c00049 · Cited by 172

Toward an AI Era: Advances in Electronic Skins

Fu, X., Cheng, W., Wan, G., Yang, Z., & Tee, B. C. K. (2024) · Chemical Reviews · doi:10.1021/acs.chemrev.4c00049 · Cited by 172

Advanced intelligent E-Skin: Multimodal sensing to AI-Driven clinical monitoring

Yu, Z., Feng, J., Dou, W., Ge, X., He, D., Zhang, M., Wang, H., & Zhou, Y. (2026) · Materials Today · doi:10.1016/j.mattod.2026.103211 · Cited by 5

Evolving Beyond Nature: AI-Driven Rapid Advancements of Bio-Inspired Electronic Skin

Quiquero, D., Noroozi, R., Wang, K., Conliffe, R., & Shi, H. (2026) · ACS Applied Materials & Interfaces · doi:10.1021/acsami.5c24192 · Cited by 2

A review of electronic skin: soft electronics and sensors for human health

Zhang, S., Li, S., Xia, Z., & Cai, K. (2019) · Journal of Materials Chemistry B · doi:10.1039/c9tb02531f · Cited by 176

Trends in Graphene-Based E-Skin and Artificial Intelligence for Biomedical Applications—A Review

Mudhulu, S., Manjunatha, C., Balaji, S., Khosla, A., & Sekhar, P. K. (2023) · IEEE Sensors Journal · doi:10.1109/jsen.2023.3294297 · Cited by 40