The Best Digital Biomarkers Papers of 2017
Open accessAbstract
The use and evaluation of digital biomarkers, objective and quantifiable measures of biology, and health collected through digital devices is growing rapidly. To highlight some of the most promising work in the field, we have compiled a list of the top digital biomarkers papers from the past year. Eligible papers reported on original research that evaluated a digital sensor (e.g., smartphone, wearable sensor, implantable device) in humans and was published in a peer-reviewed journal in 2017. Nominations were solicited from the editorial board of Digital Biomarkers and supplemented by papers the editorial team identified from Web of Science, Google Scholar, and PubMed. The editorial board then selected up to ten papers to be recognized among 28 nominations. Here, we present all of the nominated papers and profile the eight that received the most votes. The top eight papers evaluated 1,290 individuals with digital pills, smartwatches, wearable devices, and electronic inhalers in disease states ranging from dementia to diabetes and from Parkinson disease to pain.
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Current studies that test digital biomarkers are often performed with small sample sizes in the range of tens to hundreds of subjects and tend to show insufficient demographic information on sex and gender.
“current studies that test digital biomarkers are often performed with small sample sizes in the range of tens to hundreds of subjects and tend to show insufficient demographic information on sex and gender46.”
From Sex and gender differences and biases in artificial intelligence for biomedicine and healthcare (2020) · cites this paper as [46]
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Cites
Adams, J., Dinesh, K., Xiong, M., Tarolli, C. G., Sharma, S., Sheth, N., Aranyosi, A. J., Zhu, W. Y., Goldenthal, S. B., Biglan, K., et al. (2017) · Digital Biomarkers · doi:10.1159/000479018 · Cited by 3,190 · see citing works
Self-citationDigital divide: civic engagement, information poverty, and the Internet worldwide
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Dorsey, E. R., & Topol, E. J. (2016) · New England Journal of Medicine · doi:10.1056/nejmra1601705 · Cited by 1,211 · see citing works
Self-citationAutochthonous Crimean–Congo Hemorrhagic Fever in Spain
Negredo, A., Calle, F., Palencia-Herrejón, E., Mora-Rillo, M., Astray‐Mochales, J., Sánchez‐Seco, M. P., Lopez, E. B., Menárguez, J., Fernández‐Cruz, A., Sánchez, B., et al. (2017) · New England Journal of Medicine · doi:10.1056/nejmoa1615162 · Cited by 223 · see citing works
Frias, J., Virdi, N., Raja, P., Kim, Y., Savage, G., & Osterberg, L. (2017) · Journal of Medical Internet Research · doi:10.2196/jmir.7833 · Cited by 211 · see citing works
Shah, S. A., Velardo, C., Farmer, A. A., & Tarassenko, L. (2017) · Journal of Medical Internet Research · doi:10.2196/jmir.7207 · Cited by 170 · see citing works
Feasibility of large-scale deployment of multiple wearable sensors in Parkinson's disease
Silva de Lima, A. L., Hahn, T., Evers, L. J. W., de Vries, N. M., Cohen, E., Afek, M., Bataille, L., Daeschler, M., Claes, K., Boroojerdi, B., et al. (2017) · PLOS ONE · doi:10.1371/journal.pone.0189161 · Cited by 162 · see citing works
Levendowski, D. J., Ferini‐Strambi, L., Gamaldo, C. E., Cetel, M. B., Rosenberg, R., & Westbrook, P. R. (2017) · Journal of Clinical Sleep Medicine · doi:10.5664/jcsm.6618 · Cited by 152 · see citing works
Place, S., Blanch-Hartigan, D., Rubin, C., Gorrostieta, C., Mead, C., Kane, J., Marx, B. P., Feast, J., Deckersbach, T., Pentland, A. “., et al. (2017) · Journal of Medical Internet Research · doi:10.2196/jmir.6678 · Cited by 125 · see citing works
Urwyler, P., Stucki, R., Rampa, L., Müri, R. M., Mosimann, U. P., & Nef, T. (2017) · Scientific Reports · doi:10.1038/srep42084 · Cited by 116 · see citing works
Wen, D., Zhang, X., Liu, X., & Lei, J. (2017) · Journal of Medical Internet Research · doi:10.2196/jmir.6874 · Cited by 111 · see citing works
Ecological Momentary Assessment of Physical Activity: Validation Study
Knell, G., Gabriel, K. P., Businelle, M. S., Shuval, K., Wetter, D. W., & Kendzor, D. E. (2017) · Journal of Medical Internet Research · doi:10.2196/jmir.7602 · Cited by 84 · see citing works
Effect of a mobile health, sensor-driven asthma management platform on asthma control
Barrett, M., Humblet, O., Marcus, J. E., Henderson, K., Smith, T., Eid, N. S., Sublett, J. W., Renda, A. M., Nesbitt, L., Sickle, D. V., et al. (2017) · Annals of Allergy Asthma & Immunology · doi:10.1016/j.anai.2017.08.002 · Cited by 67 · see citing works
Feature selection for elderly faller classification based on wearable sensors
Howcroft, J., Kofman, J., & Lemaire, E. D. (2017) · Journal of NeuroEngineering and Rehabilitation · doi:10.1186/s12984-017-0255-9 · Cited by 66 · see citing works
Chai, P. R., Carreiro, S., Innes, B. J., Rosen, R. K., O’Cleirigh, C. M., Mayer, K. H., & Boyer, E. W. (2017) · Journal of Medical Internet Research · doi:10.2196/jmir.7050 · Cited by 63 · see citing works
Gait parameter and event estimation using smartphones
Pepa, L., Verdini, F., & Spalazzi, L. (2017) · Gait & Posture · doi:10.1016/j.gaitpost.2017.06.011 · Cited by 58 · see citing works
McKnight, R. F., Bilderbeck, A. C., Miklowitz, D. J., Hinds, C., Goodwin, G. M., & Geddes, J. R. (2017) · Journal of Affective Disorders · doi:10.1016/j.jad.2017.07.029 · Cited by 58 · see citing works
Recognition of human activities using machine learning methods with wearable sensors
Cheng, L., Guan, Y., Zhu, K., & Li, Y. (2017) · IEEE Annual Computing and Communication Workshop and Conference (CCWC) · doi:10.1109/ccwc.2017.7868369 · Cited by 50 · see citing works
Trujillo-Priego, I. A., Lane, C. J., Vanderbilt, D. L., Deng, W., Loeb, G. E., Shida-Tokeshi, J., & Smith, B. A. (2017) · Technologies · doi:10.3390/technologies5030039 · Cited by 49 · see citing works
Ligorio, G., Zanotto, D., Sabatini, A. M., & Agrawal, S. K. (2017) · Journal of Biomechanics · doi:10.1016/j.jbiomech.2017.01.024 · Cited by 46 · see citing works
Scalable Passive Sleep Monitoring Using Mobile Phones: Opportunities and Obstacles
Saeb, S., Cybulski, T. R., Kording, K. P., & Mohr, D. C. (2017) · Journal of Medical Internet Research · doi:10.2196/jmir.6821 · Cited by 46 · see citing works
Caramia, C., Bernabucci, I., D’Anna, C., Marchis, C. D., & Schmid, M. (2017) · PLoS ONE · doi:10.1371/journal.pone.0185825 · Cited by 34 · see citing works
Mitsi, G., Urrea‐Mendoza, E., Wissel, B. D., Barbopoulou, E., Dwivedi, A. K., Tsoulos, I. G., Stavrakoudis, A., Espay, A. J., & Papapetropoulos, S. (2017) · Frontiers in Neurology · doi:10.3389/fneur.2017.00273 · Cited by 33 · see citing works
Brogioli, M., Popp, W., Schneider, S., Albisser, U., Brust, A. K., Frotzler, A., Gassert, R., Curt, A. E. P., & Starkey, M. L. (2016) · Journal of Neurotrauma · doi:10.1089/neu.2016.4583 · Cited by 27 · see citing works
Portable mTBI Assessment Using Temporal and Frequency Analysis of Speech
Daudet, L., Yadav, N., Perez, M. C., Poellabauer, C., Schneider, S. L., & Huebner, A. R. (2016) · IEEE Journal of Biomedical and Health Informatics · doi:10.1109/jbhi.2016.2633509 · Cited by 25 · see citing works
The use of a smartphone application for fast lung cancer risk assessment†
Szántó, Z., Benkő, I., Jakab, L., Szalai, G., & Vereczkei, A. G. (2017) · European Journal of Cardio-Thoracic Surgery · doi:10.1093/ejcts/ezw444 · Cited by 19 · see citing works
Differentiating essential tremor and Parkinson’s disease using a wearable sensor—a pilot study
Locatelli, P., & Alimonti, D. (2017) · 2017 7th IEEE International Workshop on Advances in Sensors and Interfaces (IWASI) · doi:10.1109/iwasi.2017.7974254 · Cited by 19 · see citing works
Cheng, W.-Y., Lipsmeier, F., Scotland, A., Creagh, A., Kilchenmann, T., Jin, L., Schjodt-Eriksen, J., Wolf, D., Zhang-Schaerer, Y.-P., Garcia, I. F., et al. (2017) · 2017 IEEE Life Sciences Conference (LSC) · doi:10.1109/lsc.2017.8268169 · Cited by 13 · see citing works
Portable objective assessment of upper extremity motor function in Parkinson's disease
Chahine, L. M., Uribe, L., Hogarth, P., McNames, J., Siderowf, A., Marek, K., & Jennings, D. (2017) · Parkinsonism & Related Disorders · doi:10.1016/j.parkreldis.2017.07.017 · Cited by 4 · see citing works
Flagged first, then by citations
1 of the 30 references couldn’t be matched to a known paper.
Research works printed but not linked: 2
- Beaulieu A, Lapointe A, Givigi S, Sillins K, Lavoie A, Tilley K, Le Bel N: Network of wireless medical devices to assess the gait of rehabilitation in patients for walking and running. -2017 Annual IEEE International Systems Conference (SysCon), Montreal, QC, 2017, pp 1-8.
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Cited by
Sorted by citations
Sex and gender differences and biases in artificial intelligence for biomedicine and healthcare
Cirillo, D., Catuara-Solarz, S., Morey, C., Guney, E., Subirats, L., Mellino, S., Gigante, A., Valencia, A., Rementeria, M. J., Chadha, A. S., et al. (2020) · npj Digital Medicine · doi:10.1038/s41746-020-0288-5 · Cited by 553 · see citing works
Women's Leadership via Digital Technology and Entrepreneurship in business and society
Karyotaki, M., Bakola, L. N., Drigas, A. S., & Skianis, C. A. (2022) · Technium Social Sciences Journal · doi:10.47577/tssj.v28i1.5907 · Cited by 123 · see citing works
Izmailova, E. S., McLean, L., Hather, G., Merberg, D., Homsy, J. G., Cantor, M., Volfson, D., Bhatia, G., Perakslis, E. D., Benko, C., et al. (2019) · Clinical and Translational Science · doi:10.1111/cts.12673 · Cited by 38 · see citing works
“Arrhythmia detection via a single lead ECG device has convenience advantages relative to conventional Holter monitoring, as has been described.(3,20,21) Additionally, a comparison of the BodyGuardian device data to an independent device data, such as Holter, would help to facilitate the decision-making process around…”
MethodAdvances in Traumatic Brain Injury Biomarkers
Nishimura, K., Cordeiro, J. G., Ahmed, A. I., Yokobori, S., & Gajavelli, S. (2022) · Cureus · doi:10.7759/cureus.23804 · Cited by 23 · see citing works
“The availability of digital devices provides an opportunity to explore and adopt digital biomarkers as objective quantifiable measures [69,70].”
BackgroundGeorges-Filteau, J., & Cirillo, E. (2020) · doi:10.22541/au.158921777.79483839/v2 · Cited by 14 · see citing works
“This emerging trend known as digital bio-markers has already led to studies demonstrating predictive models with the potential for improved patient care (Snyder et al., 2018).”
BackgroundLipsky, R. H., Witkin, J. M., Shafique, H. S., Smith, J. L., Cerne, R., & Marini, A. M. (2024) · Frontiers in Neuroscience · doi:10.3389/fnins.2024.1446076 · Cited by 12 · see citing works
Digital Biomarkers in Psychiatric Research: Data Protection Qualifications in a Complex Ecosystem
Parziale, A., & Mascalzoni, D. (2022) · Frontiers in Psychiatry · doi:10.3389/fpsyt.2022.873392 · Cited by 9 · see citing works
Zetterström, A., Hämäläinen, M., Karlberg, E., Winkvist, M., Söderquist, M., Öhagen, P., Andersson, K., & Nyberg, F. (2018) · Alcohol and Alcoholism · doi:10.1093/alcalc/agy086 · Cited by 9 · see citing works
“Digital biomarkers (DBs) are increasingly used to monitor the state of different diseases (Snyder et al., 2018).”
BackgroundBiases in digital health measures
Mellino, S., Morey, C., & Rohner, C. (2022) · Elsevier eBooks · doi:10.1016/b978-0-12-821392-6.00001-7 · Cited by 6 · see citing works
Georges-Filteau, J., & Cirillo, E. (2020) · Research Square · doi:10.21203/rs.3.rs-116297/v2 · Cited by 5 · see citing works
Rainforests of wearables and insideables
Rijcken, C. A. W. (2019) · Elsevier eBooks · doi:10.1016/b978-0-12-817638-2.00010-9 · Cited by 2 · see citing works
Georges-Filteau, J., & Cirillo, E. (2020) · Research Square · doi:10.21203/rs.3.rs-116297/v1 · Cited by 1 · see citing works
(2019) · Elsevier eBooks · doi:10.1016/b978-0-12-817638-2.09988-0
Georges-Filteau, J., & Cirillo, E. (2022) · Research Square · doi:10.21203/rs.3.rs-116297/v3
Video Camera in the Ambient Assisted Living System—Health Versus Privacy
Herzog, D. J. (2022) · Springer eBooks · doi:10.1007/978-3-030-97877-8_9
Video Camera in the Ambient Assisted Living System. Health Versus Privacy
Herzog, D. J. (2022) · Advanced sciences and technologies for security applications · doi:10.1007/978-3-030-98225-6_3
Karyotaki, M., & Drigas, A. S. (2022) · Technium Sustainability · doi:10.47577/sustainability.v2i5.7410
“Interestingly, employment rates of mothers with a child under six are close to, or even higher than those with a child over six years old [1-15].”
Rijcken, C. A. W. (2023) · Elsevier eBooks · doi:10.1016/b978-0-443-13360-2.00013-7
Biswas, B. K., Sen, M., Dey, S., & Chattopadhyay, S. (2026) · Indian Journal of Pain · doi:10.4103/ijpn.ijpn_114_25
- Authors
- Snyder, C. W., Dorsey, E. R., & Atreja, A.
- Affiliations
- University of Rochester Medicine (US)
- Icahn School of Medicine at Mount Sinai (US)
- Venue
- Digital Biomarkers
- Publisher
- S. Karger AG
- Published
- 2018-05-30
- Volume
- 2
- Issue
- 2
- Pages
- 64-73
- ISSN
- 2504-110X (ISSN-L)
- PMC
- PMC7015358
- OpenAlex
- W2806112435
- Cited by
- 19
- References
- 30
- Citations by year
- 2026: 1 · 2024: 1 · 2023: 1 · 2022: 8 · 2020: 4 · 2019: 3 · 2018: 1
- FWCI
- 3.05
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- Digital Biomarkers (publishedVersion, cc-by-nc-nd)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- Topics
- Health Sciences › Health Professions › General Health Professions › Mobile Health and mHealth Applications
- Physical Sciences › Engineering › Biomedical Engineering › Non-Invasive Vital Sign Monitoring
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Context-Aware Activity Recognition Systems
- Keywords
- wearable sensors, smartphone health monitoring, biomedical implants, digital pills, smartwatches, dementia, diabetes mellitus, Parkinson's disease, pain
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