The first frontier: digital biomarkers for neurodegenerative disorders

Special Care Units and Traditional Care in Dementia: Relationship with Behavior, Cognition, Functional Status and Quality of Life - A Review

Kok, J. S., Berg, I. J., & Scherder, E. J. A. (2013) · Dementia and Geriatric Cognitive Disorders Extra · doi:10.1159/000353441 · Cited by 20,589 · see citing works

Movement Disorder Society‐sponsored revision of the Unified Parkinson's Disease Rating Scale (MDS‐UPDRS): Scale presentation and clinimetric testing results

Goetz, C. G., Tilley, B. C., Shaftman, S. R., Stebbins, G. T., Fahn, S., Martinez‐Martin, P., Poewe, W., Sampaio, C., Stern, M. B., Dodel, R., et al. (2008) · Movement Disorders · doi:10.1002/mds.22340 · Cited by 7,536 · see citing works

A new rating scale for Alzheimer's disease

(1984) · American Journal of Psychiatry · doi:10.1176/ajp.141.11.1356 · Cited by 4,175 · see citing works

Multiple Wearable Sensors in Parkinson and Huntington Disease Individuals: A Pilot Study in Clinic and at Home

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

The State of US Health, 1990-2010: Burden of Diseases, Injuries, and Risk Factors

Murray, C. J. L. (2013) · JAMA · doi:10.1001/jama.2013.13805 · Cited by 2,438 · see citing works

Effects of Coenzyme Q10 in Early Parkinson Disease: Evidence of Slowing of the Functional Decline

Shults, C. W. (2002) · Archives of Neurology · doi:10.1001/archneur.59.10.1541 · Cited by 984 · see citing works

Estimating The Cost Of New Drug Development: Is It Really $802 Million?

Adams, C., & Brantner, V. V. (2006) · Health Affairs · doi:10.1377/hlthaff.25.2.420 · Cited by 917 · see citing works

Technology in Parkinson’s disease: challenges and opportunities

Espay, A. J., Bonato, P., Nahab, F. B., Maetzler, W., Dean, J. M., Klucken, J., Eskofier, B. M., Merola, A., Horak, F., Lang, A. E., et al. (2016) · Movement Disorders · doi:10.1002/mds.26642 · Cited by 654 · see citing works

Isosorbide Mononitrate in Heart Failure with Preserved Ejection Fraction

Redfield, M. M., Anstrom, K. J., Levine, J. A., Koepp, G. A., Borlaug, B. A., Chen, H. H., LeWinter, M. M., Joseph, S. M., Shah, S. J., Semigran, M. J., et al. (2015) · New England Journal of Medicine · doi:10.1056/nejmoa1510774 · Cited by 547 · see citing works

A randomized, double-blind, futility clinical trial of creatine and minocycline in early Parkinson disease

The NINDS NET-PD Investigators (2006) · Neurology · doi:10.1212/01.wnl.0000201252.57661.e1 · Cited by 453 · see citing works

A Randomized Clinical Trial of High-Dosage Coenzyme Q10 in Early Parkinson Disease

The Parkinson Study Group QE3 Investigators, Beal, M. F., Oakes, D., Shoulson, I., Henchcliffe, C., Galpern, W. R., Haas, R., Juncos, J. L., Nutt, J. G., Voss, T., et al. (2014) · JAMA Neurology · doi:10.1001/jamaneurol.2014.131 · Cited by 410 · see citing works

Detecting and monitoring the symptoms of Parkinson's disease using smartphones: A pilot study

Arora, S., Venkataraman, V., Zhan, A., Donohue, S., Biglan, K. M., Dorsey, E. R., & Little, M. A. (2015) · Parkinsonism & Related Disorders · doi:10.1016/j.parkreldis.2015.02.026 · Cited by 387 · see citing works

The role of radiotracer imaging in Parkinson disease

Ravina, B. M., Eidelberg, D., Ahlskog, J. E., Albin, R. L., Brooks, D. J., Carbon, M., DHAWAN, V. M., Feigin, A., Fahn, S., Guttman, M., et al. (2005) · Neurology · doi:10.1212/01.wnl.0000149403.14458.7f · Cited by 372 · see citing works

A randomized, placebo-controlled trial of coenzyme Q ₁₀ and remacemide in Huntington’s disease

The Huntington Study Group (2001) · Neurology · doi:10.1212/wnl.57.3.397 · Cited by 312 · see citing works

Safety and biomarker effects of solanezumab in patients with Alzheimer's disease

Farlow, M. R., Arnold, S. E., van Dyck, C. H., Aisen, P. S. S., Snider, B. J., Porsteinsson, A. P., Friedrich, S. W., Dean, R. A., Gonzales, C., Sethuraman, G., et al. (2012) · Alzheimer s & Dementia · doi:10.1016/j.jalz.2011.09.224 · Cited by 280 · see citing works

Automated Assessment of Bradykinesia and Dyskinesia in Parkinson's Disease

Griffiths, R. I., Kotschet, K. E., Arfon, S., Xu, Z. M., Johnson, W. G., Drago, J., Evans, A. H., Kempster, P. A., Raghav, S., & Horne, M. K. (2012) · Journal of Parkinson s Disease · doi:10.3233/jpd-2012-11071 · Cited by 278 · see citing works

Unified Parkinson's disease rating scale motor examination: Are ratings of nurses, residents in neurology, and movement disorders specialists interchangeable?

Post, B., Merkus, M. P., de Bie, R. M. A., de Haan, R. J., & Speelman, J. D. (2005) · Movement Disorders · doi:10.1002/mds.20640 · Cited by 264 · see citing works

Utilizing a Personal Smartphone Custom App to Assess the Patient Health Questionnaire-9 (PHQ-9) Depressive Symptoms in Patients With Major Depressive Disorder

Torous, J., Staples, P., Shanahan, M., Lin, C., Peck, P., Keshavan, M., & Onnela, J.-P. (2015) · JMIR Mental Health · doi:10.2196/mental.3889 · Cited by 258 · see citing works

Effect of Creatine Monohydrate on Clinical Progression in Patients With Parkinson Disease

Kieburtz, K. D., Tilley, B. C., Elm, J. J., Babcock, D., Hauser, R. A., Ross, G. W., Augustine, A. H., Augustine, E., Aminoff, M. J., Bodis-Wollner, I. G., et al. (2015) · JAMA · doi:10.1001/jama.2015.120 · Cited by 248 · see citing works

Dexpramipexole versus placebo for patients with amyotrophic lateral sclerosis (EMPOWER): a randomised, double-blind, phase 3 trial

Cudkowicz, M., van den Berg, L. H., Shefner, J. M., Mitsumoto, H., Mora, J. S., Ludolph, A. C., Hardiman, O. M., Bozik, M. E., Ingersoll, E. W., Archibald, D., et al. (2013) · The Lancet Neurology · doi:10.1016/s1474-4422(13)70221-7 · Cited by 232 · see citing works

A systematic review of the characteristics and validity of monitoring technologies to assess Parkinson’s disease

Godinho, C., Domingos, J., Cunha, G., Santos, A. T., Fernandes, R. M., Abreu, D., Gonçalves, N., Matthews, H., Isaacs, T., Duffen, J., et al. (2016) · Journal of NeuroEngineering and Rehabilitation · doi:10.1186/s12984-016-0136-7 · Cited by 226 · see citing works

A randomized clinical trial of coenzyme Q 10 and GPI-1485 in early Parkinson disease

The NINDS NET-PD Investigators (2007) · Neurology · doi:10.1212/01.wnl.0000250355.28474.8e · Cited by 219 · see citing works

Multiple sclerosis: the role of MR imaging.

Ge, Y. (2006) · PubMed Central · Cited by 196 · see citing works

The effects of dexpramipexole (KNS-760704) in individuals with amyotrophic lateral sclerosis

Cudkowicz, M., Bozik, M. E., Ingersoll, E. W., Miller, R. G., Mitsumoto, H., Shefner, J. M., Moore, D. H., Schoenfeld, D., Mather, J. L., Archibald, D., et al. (2011) · Nature Medicine · doi:10.1038/nm.2579 · Cited by 178 · see citing works

Pridopidine for the treatment of motor function in patients with Huntington's disease (MermaiHD): a phase 3, randomised, double-blind, placebo-controlled trial

de Yébenes, J. G., Landwehrmeyer, G. B., Squitieri, F., Reilmann, R., Rosser, A., Barker, R. A., Carsten Saft, C., Magnet, M. K., Sword, A., Rembratt, Å., et al. (2011) · The Lancet Neurology · doi:10.1016/s1474-4422(11)70233-2 · Cited by 171 · see citing works

A clinical view on the development of technology‐based tools in managing Parkinson's disease

Maetzler, W., Klucken, J., & Horne, M. (2016) · Movement Disorders · doi:10.1002/mds.26673 · Cited by 162 · see citing works

The validity of the GaitRite and the Functional Ambulation Performance scoring system in the analysis of Parkinson gait1

Nelson, A. J., Zwick, D., Brody, S., Doran, C., Pulver, L., Rooz, G., Sadownick, M., Nelson, R. M., & Rothman, J. (2002) · Neurorehabilitation · doi:10.3233/nre-2002-17312 · Cited by 158 · see citing works

Clinician versus machine: Reliability and responsiveness of motor endpoints in Parkinson's disease

Heldman, D. A., Espay, A. J., LeWitt, P. A., & Giuffrida, J. P. (2014) · Parkinsonism & Related Disorders · doi:10.1016/j.parkreldis.2014.02.022 · Cited by 156 · see citing works

A randomized, double-blind, placebo-controlled trial of coenzyme Q10 in Huntington disease

McGarry, A. J., McDermott, M., Kieburtz, K. D., de Blieck, E. A., Beal, F. M., Marder, K. S., Ross, C. A., Shoulson, I., Gilbert, P. R., Mallonee, W. M., et al. (2016) · Neurology · doi:10.1212/wnl.0000000000003478 · Cited by 139 · see citing works

A randomized, double‐blind, placebo‐controlled trial of pridopidine in Huntington's disease

The Huntington Study Group HART Investigators (2013) · Movement Disorders · doi:10.1002/mds.25362 · Cited by 127 · see citing works

Natural History of Huntington Disease

Dorsey, E. R. (2013) · JAMA Neurology · doi:10.1001/jamaneurol.2013.4408 · Cited by 124 · see citing works

Feasibility of home-based automated Parkinson's disease motor assessment

Mera, T. O., Heldman, D. A., Espay, A. J., Payne, M., & Giuffrida, J. P. (2011) · Journal of Neuroscience Methods · doi:10.1016/j.jneumeth.2011.09.019 · Cited by 111 · see citing works

A Randomized, Placebo-Controlled Trial of Latrepirdine in Huntington Disease

Kieburtz, K. D. (2010) · Archives of Neurology · doi:10.1001/archneurol.2009.334 · Cited by 92 · see citing works

What Engineering Technology Could Do for Quality of Life in Parkinson's Disease: A Review of Current Needs and Opportunities

Stamford, J. A., Schmidt, P. N., & Friedl, K. E. (2015) · IEEE Journal of Biomedical and Health Informatics · doi:10.1109/jbhi.2015.2464354 · Cited by 86 · see citing works

A randomized, placebo‐controlled trial of AFQ056 for the treatment of chorea in Huntington's disease

Reilmann, R., Rouzade‐Dominguez, M., Carsten Saft, C., Süßmuth, S. D., Priller, J., Rosser, A., Rickards, H. E., Schöls, L. J., Pezous, N., Gasparini, F., et al. (2015) · Movement Disorders · doi:10.1002/mds.26174 · Cited by 79 · see citing works

Unified Parkinson’s Disease Rating Scale‐Motor Exam: inter‐rater reliability of advanced practice nurse and neurologist assessments

Palmer, J. L., Coats, M. A., Roe, C. M., Hanko, S. M., Xiong, C., & Morris, J. C. (2010) · Journal of Advanced Nursing · doi:10.1111/j.1365-2648.2010.05313.x · Cited by 78 · see citing works

Daytime sleep in Parkinson's disease measured by episodes of immobility

Kotschet, K. E., Johnson, W. G., McGregor, S., Kettlewell, J., Kyoong, A., O’Driscoll, D. M., Turton, A. R., Griffiths, R. I., & Horne, M. K. (2014) · Parkinsonism & Related Disorders · doi:10.1016/j.parkreldis.2014.02.011 · Cited by 73 · see citing works

Sleep disorders in neurodegenerative diseases

Raggi, A., & Ferri, R. (2010) · European Journal of Neurology · doi:10.1111/j.1468-1331.2010.03034.x · Cited by 68 · see citing works

Wearable Sensors in Huntington Disease: A Pilot Study

Andrzejewski, K. L., Dowling, A. V., Stamler, D. A., Felong, T. J., Harris, D. A., Wong, C., Cai, H. W., Reilmann, R., Little, M. A., Gwin, J. T., et al. (2016) · Journal of Huntington s Disease · doi:10.3233/jhd-160197 · Cited by 67 · see citing works

Correlation of Quantitative Motor State Assessment Using a Kinetograph and Patient Diaries in Advanced PD: Data from an Observational Study

Ossig, C., Gandor, F., Fauser, M., Bosredon, C., Churilov, L. P., Reichmann, H., Horne, M. K., Ebersbach, G., & Storch, A. (2016) · PLoS ONE · doi:10.1371/journal.pone.0161559 · Cited by 64 · see citing works

The Impact of Exercise, Cognitive Activities, and Socialization on Cognitive Function

Jedrziewski, M. K., Ewbank, D. C., Wang, H., & Trojanowski, J. Q. (2014) · American Journal of Alzheimer s Disease & Other Dementias® · doi:10.1177/1533317513518646 · Cited by 54 · see citing works

A Randomized, Double-blind, Placebo-Controlled Study of Latrepirdine in Patients With Mild to Moderate Huntington Disease

(2012) · JAMA Neurology · doi:10.1001/2013.jamaneurol.382 · Cited by 53 · see citing works

Clinical trials in Huntington's disease: Interventions in early clinical development and newer methodological approaches

Sampaio, C., Borowsky, B., & Reilmann, R. (2014) · Movement Disorders · doi:10.1002/mds.26021 · Cited by 50 · see citing works

Interpretation of clinical trials that stopped early

Viele, K., McGlothlin, A., & Broglio, K. (2016) · JAMA · doi:10.1001/jama.2016.2628 · Cited by 48 · see citing works

Digitomotography in Parkinson’s Disease: A Cross-Sectional and Longitudinal Study

Maetzler, W., Ellerbrock, M., Heger, T., Saß, C., Berg, D., & Reilmann, R. (2015) · PLoS ONE · doi:10.1371/journal.pone.0123914 · Cited by 24 · see citing works

WiiPD — An approach for the objective home assessment of Parkinson's disease

Synnott, J., Chen, L., Nugent, C., & Moore, G. (2011) · Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) · doi:10.1109/iembs.2011.6090666 · Cited by 15 · see citing works

Joining forces to fight neurodegenerative diseases

Neurology, T. L. (2013) · The Lancet Neurology · doi:10.1016/s1474-4422(13)70004-8 · Cited by 8 · see citing works

Digital biomarkers for Alzheimer’s disease: the mobile/wearable devices opportunity

Kourtis, L. C., Regele, O. B., Wright, J. M., & Jones, G. B. (2019) · npj Digital Medicine · doi:10.1038/s41746-019-0084-2 · Cited by 476 · see citing works

Digital Twins for Multiple Sclerosis

Voigt, I., Inojosa, H., Dillenseger, A., Haase, R., Akgün, K., & Ziemssen, T. (2021) · Frontiers in Immunology · doi:10.3389/fimmu.2021.669811 · Cited by 279 · see citing works

Evaluation of smartphone‐based testing to generate exploratory outcome measures in a phase 1 Parkinson's disease clinical trial

Lipsmeier, F., Taylor, K. I., Kilchenmann, T., Wolf, D., Scotland, A., Schjodt‐Eriksen, J., Cheng, W., Fernandez‐Garcia, I., Siebourg‐Polster, J., Jin, L., et al. (2018) · Movement Disorders · doi:10.1002/mds.27376 · Cited by 266 · see citing works

Teleneurology and mobile technologies: the future of neurological care

Dorsey, E. R., Glidden, A. M., Holloway, M. R., Birbeck, G. L., & Schwamm, L. H. (2018) · Nature Reviews Neurology · doi:10.1038/nrneurol.2018.31 · Cited by 258 · see citing works

Smartwatch inertial sensors continuously monitor real-world motor fluctuations in Parkinson’s disease

Powers, R., Etezadi‐Amoli, M., Arnold, E. M., Kianian, S., Mance, I., Gibiansky, M. L., Trietsch, D., Alvarado, A. S., Kretlow, J. D., Herrington, T. M., et al. (2021) · Science Translational Medicine · doi:10.1126/scitranslmed.abd7865 · Cited by 204 · see citing works

Therapeutic approaches to Huntington disease: from the bench to the clinic

Caron, N. S., Dorsey, E. R., & Hayden, M. R. (2018) · Nature Reviews Drug Discovery · doi:10.1038/nrd.2018.133 · Cited by 161 · see citing works

Translational precision medicine: an industry perspective

Hartl, D., Luca, V. D., Kostikova, A., Laramie, J. M., Kennedy, S., Ferrero, E., Siegel, R. W., Fink, M., Ahmed, S., Millholland, J. M., et al. (2021) · Journal of Translational Medicine · doi:10.1186/s12967-021-02910-6 · Cited by 153 · see citing works

Development of digital biomarkers for resting tremor and bradykinesia using a wrist-worn wearable device

Mahadevan, N., Demanuele, C., Zhang, H., Volfson, D., Ho, B., Erb, M. K., & Patel, S. (2020) · npj Digital Medicine · doi:10.1038/s41746-019-0217-7 · Cited by 138 · see citing works

Machine learning and digital biomarkers can detect early stages of neurodegenerative diseases

Chudzik, A., Śledzianowski, A., & Przybyszewski, A. W. (2024) · Sensors · doi:10.3390/s24051572 · Cited by 122 · see citing works

Digital Biomarkers in Multiple Sclerosis

Dillenseger, A., Weidemann, M. L., Trentzsch, K., Inojosa, H., Haase, R., Schriefer, D., Voigt, I., Scholz, M., Akgün, K., & Ziemssen, T. (2021) · Brain Sciences · doi:10.3390/brainsci11111519 · Cited by 121 · see citing works

Walking on common ground: a cross-disciplinary scoping review on the clinical utility of digital mobility outcomes

Polhemus, A. M., Delgado‐Ortiz, L., Brittain, G., Chynkiamis, N., Salis, F., Gaßner, H., Groß, M., Kirk, C., Rossanigo, R., Taraldsen, K., et al. (2021) · npj Digital Medicine · doi:10.1038/s41746-021-00513-5 · Cited by 101 · see citing works

Using a smartwatch and smartphone to assess early Parkinson’s disease in the WATCH-PD study

Adams, J. L., Kangarloo, T., Tracey, B., O’Donnell, P., Volfson, D., Latzman, R. D., Zach, N., Alexander, R., Bergethon, P., Cosman, J., et al. (2023) · npj Parkinson's Disease · doi:10.1038/s41531-023-00497-x · Cited by 98 · see citing works

Detecting the impact of subject characteristics on machine learning-based diagnostic applications

Chaibub Neto, E., Pratap, A., Perumal, T. M., Tummalacherla, M., Snyder, P., Bot, B. M., Trister, A. D., Friend, S. H., Mangravite, L., & Omberg, L. (2019) · npj Digital Medicine · doi:10.1038/s41746-019-0178-x · Cited by 83 · see citing works

Connecting real-world digital mobility assessment to clinical outcomes for regulatory and clinical endorsement–the Mobilise-D study protocol

Mikolaizak, A. S., Rochester, L., Maetzler, W., Sharrack, B., Demeyer, H., Mazzà, C., Caulfield, B., García‐Aymerich, J., Vereijken, B., Arnera, V., et al. (2022) · PLoS ONE · doi:10.1371/journal.pone.0269615 · Cited by 94 · see citing works

Stride Velocity 95th Centile: Insights into Gaining Regulatory Qualification of the First Wearable-Derived Digital Endpoint for use in Duchenne Muscular Dystrophy Trials

Servais, L., Yen, K., Guridi, M., Lukawy, J., Vissière, D., & Strijbos, P. J. L. M. (2021) · Journal of Neuromuscular Diseases · doi:10.3233/jnd-210743 · Cited by 84 · see citing works

Applied Machine Learning Techniques to Diagnose Voice-Affecting Conditions and Disorders: Systematic Literature Review

Idrisoglu, A., Dallora, A. L., Anderberg, P., & Berglund, J. S. (2023) · Journal of Medical Internet Research · doi:10.2196/46105 · Cited by 83 · see citing works

Alzheimer's disease digital biomarkers multidimensional landscape and AI model scoping review

Qi, W., Zhu, X., Wang, B., Shi, Y., Dong, C., Shen, S., Li, J., Zhang, K., He, Y., Zhao, M., et al. (2025) · npj Digital Medicine · doi:10.1038/s41746-025-01640-z · Cited by 78 · see citing works

Ethical issues when using digital biomarkers and artificial intelligence for the early detection of dementia

Ford, E. M., Milne, R., & Curlewis, K. (2023) · Wiley Interdisciplinary Reviews Data Mining and Knowledge Discovery · doi:10.1002/widm.1492 · Cited by 80 · see citing works

Using a smartwatch and smartphone to assess early Parkinson’s disease in the WATCH-PD study over 12 months

Adams, J., Kangarloo, T., Gong, Y., Khachadourian, V., Tracey, B., Volfson, D., Latzman, R. D., Cosman, J. D., Edgerton, J. R., Anderson, D. E., et al. (2024) · npj Parkinson s Disease · doi:10.1038/s41531-024-00721-2 · Cited by 77 · see citing works

Definitions of digital biomarkers: a systematic mapping of the biomedical literature

Alonso, A. K. M., Hirt, J., Woelfle, T., Janiaud, P., & Hemkens, L. G. (2024) · BMJ Health & Care Informatics · doi:10.1136/bmjhci-2023-100914 · Cited by 75 · see citing works

Clinical Trial Endpoints and Their Clinical Meaningfulness in Early Stages of Alzheimer's Disease

Cohen, S., Cummings, J. L., Knox, S., Potashman, M. H., & Harrison, J. (2022) · The Journal of Prevention of Alzheimer s Disease · doi:10.14283/jpad.2022.41 · Cited by 70 · see citing works

Digital Biomarker–Based Studies: Scoping Review of Systematic Reviews

Motahari-Nezhad, H., Fgaier, M., Abid, M. M., Péntek, M., Gulàcsi, L., & Zrubka, Z. (2022) · JMIR mhealth and uhealth · doi:10.2196/35722 · Cited by 68 · see citing works

Deep Phenotyping of Parkinson’s Disease

Dorsey, E. R., Omberg, L., Waddell, E. M., Adams, J., Adams, R., Ali, M. R., Amodeo, K., Arky, A., Augustine, E. F., Dinesh, K., et al. (2020) · Journal of Parkinson s Disease · doi:10.3233/jpd-202006 · Cited by 63 · see citing works

The PARK Framework for Automated Analysis of Parkinson's Disease Characteristics

Langevin, R., Ali, M. R., Sen, T., Snyder, C., Myers, T. L., Dorsey, E. R., & Hoque, M. E. (2019) · Proceedings of the ACM on Interactive Mobile Wearable and Ubiquitous Technologies · doi:10.1145/3328925 · Cited by 59 · see citing works

Detection of Mild Cognitive Impairment Through Natural Language and Touchscreen Typing Processing

Ntracha, A., Iakovakis, D., Hadjidimitriou, S., Charisis, V. S., Tsolaki, M., & Hadjileontiadis, L. J. (2020) · Frontiers in Digital Health · doi:10.3389/fdgth.2020.567158 · Cited by 55 · see citing works

Digital Health Technology for Real-World Clinical Outcome Measurement Using Patient-Generated Data: Systematic Scoping Review

Pyper, E., Ruggiero, S. M., Hartmann‐Boyce, J., & powell, J. A. (2023) · Journal of Medical Internet Research · doi:10.2196/46992 · Cited by 59 · see citing works

Digital gait biomarkers in Parkinson’s disease: susceptibility/risk, progression, response to exercise, and prognosis

Mancini, M., Afshari, M., Almeida, Q. J., Huffmaster, S. L. A., Balfany, K., Camicioli, R. M., Christiansen, C. L., Dale, M. L., Dibble, L. E., Earhart, G. M., et al. (2025) · npj Parkinson s Disease · doi:10.1038/s41531-025-00897-1 · Cited by 52 · see citing works

Digital Progression Biomarkers as Novel Endpoints in Clinical Trials: A Multistakeholder Perspective

Stephenson, D. T., Badawy, R., Mathur, S., Tome, M. B., & Rochester, L. (2021) · Journal of Parkinson s Disease · doi:10.3233/jpd-202428 · Cited by 52 · see citing works

Passive Monitoring at Home: A Pilot Study in Parkinson Disease

Kabelac, Z., Tarolli, C. G., Snyder, C., Feldman, B., Glidden, A. M., Hsu, C.-Y., Hristov, R., Dorsey, E. R., & Katabi, D. (2019) · Digital Biomarkers · doi:10.1159/000498922 · Cited by 51 · see citing works

Walking-related digital mobility outcomes as clinical trial endpoint measures: protocol for a scoping review

Polhemus, A. M., Bergquist, R., de Basea, M. B., Brittain, G., Buttery, S. C., Chynkiamis, N., Costa, G. D., Delgado‐Ortiz, L., Demeyer, H., Emmert, K., et al. (2020) · BMJ Open · doi:10.1136/bmjopen-2020-038704 · Cited by 44 · see citing works

Screening of Parkinsonian subtle fine-motor impairment from touchscreen typing via deep learning

Iakovakis, D., Chaudhuri, К. R., Klingelhoefer, L., Bostantjopoulou, S., Katsarou, Z., Trivedi, D., Reichmann, H., Hadjidimitriou, S., Charisis, V. S., & Hadjileontiadis, L. J. (2020) · Scientific Reports · doi:10.1038/s41598-020-69369-1 · Cited by 43 · see citing works

A systems approach towards remote health-monitoring in older adults: Introducing a zero-interaction digital exhaust

Schütz, N., Knobel, S. E. J., Botros, A., Single, M., Pais, B., Santschi, V., Gática-Pérez, D., Buluschek, P., Urwyler, P., Gerber, S. M., et al. (2022) · npj Digital Medicine · doi:10.1038/s41746-022-00657-y · Cited by 38 · see citing works

Digital Biomarkers for Neuromuscular Disorders: A Systematic Scoping Review

Youn, B.-Y., Ko, Y., Moon, S., Lee, J., Ko, S.-G., & Kim, J.-Y. (2021) · Diagnostics · doi:10.3390/diagnostics11071275 · Cited by 37 · see citing works

A Remote Digital Monitoring Platform to Assess Cognitive and Motor Symptoms in Huntington Disease: Cross-sectional Validation Study

Lipsmeier, F., Simillion, C., Bamdadian, A., Tortelli, R., Byrne, L. M., Zhang, Y., Wolf, D., Smith, A. V., Czech, C., Gossens, C., et al. (2022) · Journal of Medical Internet Research · doi:10.2196/32997 · Cited by 36 · see citing works

Development of Neurodegenerative Disease Diagnosis and Monitoring from Traditional to Digital Biomarkers

Song, J., Cho, E., Lee, H., Lee, S., Kim, S., & Kim, J. (2025) · Biosensors · doi:10.3390/bios15020102 · Cited by 37 · see citing works

Digital Twin Cognition: AI-Biomarker Integration in Biomimetic Neuropsychology

Gkintoni, E., & Halkiopoulos, C. (2025) · Biomimetics · doi:10.3390/biomimetics10100640 · Cited by 41 · see citing works

Machine Learning and the Digital Measurement of Psychological Health

Galatzer‐Levy, I. R., & Onnela, J.-P. “. (2023) · Annual Review of Clinical Psychology · doi:10.1146/annurev-clinpsy-080921-073212 · Cited by 35 · see citing works

Wearable Sensor-Based Assessments for Remotely Screening Early-Stage Parkinson’s Disease

Johnson, S., Kantartjis, M., Severson, J., Dorsey, R. E., Adams, J., Kangarloo, T., Kostrzebski, M. A., Best, A., Merickel, M., Amato, D., et al. (2024) · Sensors · doi:10.3390/s24175637 · Cited by 34 · see citing works

Measuring Saccade Latency Using Smartphone Cameras

Lai, H.-Y., Saavedra-Peña, G., Sodini, C. G., Sze, V., & Heldt, T. (2019) · IEEE Journal of Biomedical and Health Informatics · doi:10.1109/jbhi.2019.2913846 · Cited by 34 · see citing works

Overcoming Alzheimer’s Disease Stigma by Leveraging Artificial Intelligence and Blockchain Technologies

Pilozzi, A. R., & Huang, X. (2020) · Brain Sciences · doi:10.3390/brainsci10030183 · Cited by 35 · see citing works

Design of a virtual longitudinal observational study in Parkinson’s disease (AT‐HOME PD)

Schneider, R. B., Omberg, L., Macklin, E. A., Daeschler, M., Bataille, L., Anthwal, S., Myers, T. L., Baloga, E., Duquette, S., Snyder, P., et al. (2020) · Annals of Clinical and Translational Neurology · doi:10.1002/acn3.51236 · Cited by 32 · see citing works

The CloudUPDRS smartphone software in Parkinson’s study: cross-validation against blinded human raters

Jha, A., Menozzi, E., Oyekan, R., Latorre, A., Mulroy, E., Schreglmann, S. R., Stamate, C., Daskalopoulos, I., Küppers, S., Luchini, M. U., et al. (2020) · npj Parkinson s Disease · doi:10.1038/s41531-020-00135-w · Cited by 30 · see citing works

Assessing Social Anxiety Through Digital Biomarkers Embedded in a Gaming Task

Dechant, M., Frommel, J., & Mandryk, R. L. (2021) · CHI Conference on Human Factors in Computing Systems · doi:10.1145/3411764.3445238 · Cited by 31 · see citing works

Ethical Considerations of Digital Phenotyping from the Perspective of a Healthcare Practitioner

Dagum, P., & Montag, C. (2019) · Studies in neuroscience, psychology and behavioral economics · doi:10.1007/978-3-030-31620-4_2 · Cited by 30 · see citing works

Validation of the Remote Automated ki:e Speech Biomarker for Cognition in Mild Cognitive Impairment: Verification and Validation following DiME V3 Framework

Tröger, J., Baykara, E., Zhao, J., ter Huurne, D., Possemis, N., Mallick, E., Schäfer, S., Schwed, L., Mina, M. M., Linz, N., et al. (2022) · Digital Biomarkers · doi:10.1159/000526471 · Cited by 32 · see citing works

A Longitudinal Wearable Sensor Study in Huntington’s Disease

Dinesh, K., Snyder, C. W., Xiong, M., Tarolli, C. G., Sharma, S., Dorsey, E. R., Gaurav Sharma, A., & Adams, J. (2019) · Journal of Huntington s Disease · doi:10.3233/jhd-190375 · Cited by 28 · see citing works

Detecting Mild Cognitive Impairment via Digital Biomarkers of Cognitive Performance Found in Klondike Solitaire: A Machine-Learning Study

Gielis, K., Abeele, M.-E. V., Verbert, K., Tournoy, J., Vos, M. D., & Abeele, V. V. (2021) · Digital Biomarkers · doi:10.1159/000514105 · Cited by 27 · see citing works

Current Technology Developments Can Improve the Quality of Research and Level of Evidence for Rehabilitation Interventions: A Narrative Review

Bonnechère, B., Timmermans, A. A. A., & Michiels, S. (2023) · Sensors · doi:10.3390/s23020875 · Cited by 27 · see citing works

Translating cell therapies for neurodegenerative diseases: Huntington’s disease as a model disorder

Rosser, A., Busse, M. E., Gray, W., Badin, R. A., Perrier, A. L., Wheelock, V., Cozzi, E., Perpiñá, U., Salado-Manzano, C., Mills, L. J., et al. (2022) · Brain · doi:10.1093/brain/awac086 · Cited by 26 · see citing works

Tablet-Based Application for Objective Measurement of Motor Fluctuations in Parkinson Disease

Wissel, B. D., Mitsi, G., Dwivedi, A. K., Papapetropoulos, S., Larkin, S., Castellanos, J. R. L., Shanks, E., Duker, A. P., Rodriguez‐Porcel, F. E., Vaughan, J. E., et al. (2018) · Digital Biomarkers · doi:10.1159/000485468 · Cited by 26 · see citing works

A Sensor-Based Perspective in Early-Stage Parkinson’s Disease: Current State and the Need for Machine Learning Processes

Krokidis, M. G., Dimitrakopoulos, G. Ν., Vrahatis, A. G., Tzouvelekis, C., Drakoulis, D., Papavassileiou, F., Exarchos, T. P., & Vlamos, P. (2022) · Sensors · doi:10.3390/s22020409 · Cited by 25 · see citing works

Navigating Neurodegeneration: Integrating Biomarkers, Neuroinflammation, and Imaging in Parkinson’s, Alzheimer’s, and Motor Neuron Disorders

Tanaka, M., Battaglia, S., & Liloia, D. (2025) · Biomedicines · doi:10.3390/biomedicines13051045 · Cited by 24 · see citing works

Digital biomarkers and sex impacts in Alzheimer’s disease management — potential utility for innovative 3P medicine approach

Harms, R., Ferrari, A., Meier, I. B., Martínková, J., Santus, E., Marino, N., Cirillo, D., Mellino, S., Catuara‐Solarz, S., Tarnanas, I., et al. (2022) · The EPMA Journal · doi:10.1007/s13167-022-00284-3 · Cited by 23 · see citing works

An automatic measure for speech intelligibility in dysarthrias—validation across multiple languages and neurological disorders

Tröger, J., Dörr, F., Schwed, L., Linz, N., König, A., Thies, T., Barbe, M. T., Orozco‐Arroyave, J. R., & Rusz, J. (2024) · Frontiers in Digital Health · doi:10.3389/fdgth.2024.1440986 · Cited by 22 · see citing works

Digital assessment of speech in Huntington disease

Nunes, A. S., Pawlik, M. E., Mishra, R. K., Waddell, E. M., Coffey, M., Tarolli, C. G., Schneider, R. B., Dorsey, E. R., Vaziri, A., & Adams, J. (2024) · Frontiers in Neurology · doi:10.3389/fneur.2024.1310548 · Cited by 20 · see citing works

Incorporating Wearable Technology for Enhanced Rehabilitation Monitoring after Hip and Knee Replacement

Lebleu, J., Daniels, K., Pauwels, A., Dekimpe, L., Mapinduzi, J., Poilvache, H., & Bonnechère, B. (2024) · Sensors · doi:10.3390/s24041163 · Cited by 20 · see citing works

Dissecting Digital Card Games to Yield Digital Biomarkers for the Assessment of Mild Cognitive Impairment: Methodological Approach and Exploratory Study

Gielis, K., Abeele, M.-E. V., Croon, R. D., Dierick, P., Ferreira-Brito, F., Assche, L. V., Verbert, K., Tournoy, J., & Abeele, V. V. (2021) · JMIR Serious Games · doi:10.2196/18359 · Cited by 20 · see citing works

Digital Biomarkers for Neurodegenerative Disease

Erickson, C. M., Wexler, A., & Largent, E. A. (2025) · JAMA Neurology · doi:10.1001/jamaneurol.2024.3533 · Cited by 19 · see citing works

Biomarkers of Parkinson's disease in perspective of early diagnosis and translation of neurotrophic therapies

Tuominen, R. K., & Renko, J. (2024) · Basic & Clinical Pharmacology & Toxicology · doi:10.1111/bcpt.14042 · Cited by 18 · see citing works

A Smartphone Application as an Exploratory Endpoint in a Phase 3 Parkinson’s Disease Clinical Trial: A Pilot Study

Page, A., Yung, N. C. W., Auinger, P., Venuto, C. S., Glidden, A. M., Macklin, E. A., Omberg, L., Schwarzschild, M. A., & Dorsey, E. R. (2022) · Digital Biomarkers · doi:10.1159/000521232 · Cited by 17 · see citing works

NPT520-34 improves neuropathology and motor deficits in a transgenic mouse model of Parkinson’s disease

Khan, A., Johnson, R., Wittmer, C., Maile, M., Tatsukawa, K. J., Wong, J. L., Gill, M. B., Stocking, E. M., Natala, S. R., Paulino, A., et al. (2021) · Brain · doi:10.1093/brain/awab214 · Cited by 17 · see citing works

Screening for Mild Cognitive Impairment Using a Machine Learning Classifier and the Remote Speech Biomarker for Cognition: Evidence from Two Clinically Relevant Cohorts

Schäfer, S., Mallick, E., Schwed, L., König, A., Zhao, J., Linz, N., Bodin, T. H., Skoog, J., Possemis, N., ter Huurne, D., et al. (2022) · Journal of Alzheimer s Disease · doi:10.3233/jad-220762 · Cited by 16 · see citing works

Quantifying the Benefits of Digital Biomarkers and Technology-Based Study Endpoints in Clinical Trials: Project Moneyball

Mori, H., Wiklund, S. J., & Zhang, J. Y. (2022) · Digital Biomarkers · doi:10.1159/000525255 · Cited by 16 · see citing works

Rapid development of an integrated remote programming platform for neuromodulation systems through the biodesign process

Silburn, P. A., DeBates, S., Tomlinson, T., Schwark, J., Creek, G., Patel, H., Punnoose, A., Cheeran, B., Ross, E., Lautner, D., et al. (2022) · Scientific Reports · doi:10.1038/s41598-022-06098-7 · Cited by 15 · see citing works

Can composite digital monitoring biomarkers come of age? A framework for utilization

Kovalchick, C., Sirkar, R., Regele, O. B., Kourtis, L. C., Schiller, M., Wolpert, H. A., Alden, R. G., Jones, G. B., & Wright, J. M. (2017) · Journal of Clinical and Translational Science · doi:10.1017/cts.2018.4 · Cited by 15 · see citing works

Screening for Mild Cognitive Impairment through Digital Biomarkers of Cognitive Performance in Games

Gielis, K. (2019) · Annual Symposium on Computer-Human Interaction in Play · doi:10.1145/3341215.3356332 · Cited by 14 · see citing works

The Development of Explicit and Implicit Game-Based Digital Behavioral Markers for the Assessment of Social Anxiety

Dechant, M., Frommel, J., & Mandryk, R. L. (2021) · Frontiers in Psychology · doi:10.3389/fpsyg.2021.760850 · Cited by 14 · see citing works

Digital Biomarkers for Parkinson Disease: Bibliometric Analysis and a Scoping Review of Deep Learning for Freezing of Gait

Qi, W., Shen, S., Dong, C., Zhao, M., Zang, S., Zhu, X., Li, J., Wang, B., Shi, Y., Dong, Y., et al. (2025) · Journal of Medical Internet Research · doi:10.2196/71560 · Cited by 16 · see citing works

A novel framework to estimate cognitive impairment via finger interaction with digital devices

Holmes, A. A., Tripathi, S., Katz, E. R., Mondesire-Crump, I., Mahajan, R., Ritter, A. R., Arroyo‐Gallego, T., & Giancardo, L. (2022) · Brain Communications · doi:10.1093/braincomms/fcac194 · Cited by 13 · see citing works

Exploring a multimodal approach for utilizing digital biomarkers for childhood mental health screening

Choo, M., Park, D., Cho, M., Bae, S., Kim, J., & Han, D. H. (2024) · Frontiers in Psychiatry · doi:10.3389/fpsyt.2024.1348319 · Cited by 11 · see citing works

Modernizing the Staging of Parkinson Disease Using Digital Health Technology

Templeton, J. M., Poellabauer, C., Schneider, S. L., Rahimi, M., Braimoh, T., Tadamarry, F., Margolesky, J. H., Burke, S. L., & Masry, Z. A. (2025) · Journal of Medical Internet Research · doi:10.2196/63105 · Cited by 12 · see citing works

Collecting Digital Biomarkers on Cognitive Health Through Computer Vision and Gameplay: an Image Processing Toolkit for Card Games

Gielis, K., Kennes, J., Dobbeleer, C. D., Puttemans, S., & Abeele, V. V. (2019) · IEEE International Conference on Healthcare Informatics (ICHI) · doi:10.1109/ichi.2019.8904511 · Cited by 11 · see citing works

Online clinical tools to support the use of new plasma biomarker diagnostic technology in the assessment of Alzheimer’s disease: a narrative review

Hazan, J., Liu, K. Y., Fox, N. C., & Howard, R. J. (2023) · Brain Communications · doi:10.1093/braincomms/fcad322 · Cited by 10 · see citing works

Considerations on How to Prevent Parkinson’s Disease Through Exercise

Oosterhof, T. H., Darweesh, S. K. L., Bloem, B. R., & de Vries, N. M. (2024) · Journal of Parkinson s Disease · doi:10.3233/jpd-240091 · Cited by 11 · see citing works

User-centered design of feedback regarding health-related behaviors derived from wearables: An approach targeting older adults and persons living with neurodegenerative disease

Ooteghem, K. V., Godkin, F. E., Thai, V., Beyer, K. B., Cornish, B. F., Weber, K. S., Bernstein, H., Kheiri, S. O., Swartz, R. H., Tan, B., et al. (2023) · Digital Health · doi:10.1177/20552076231179031 · Cited by 9 · see citing works

Characteristics and Applications of Technology-Aided Hand Functional Assessment: A Systematic Review

Mennella, C., Alloisio, S., Novellino, A., & Viti, F. (2021) · Sensors · doi:10.3390/s22010199 · Cited by 9 · 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

Advancing Digital Medicine with Wearables in the Wild

McGinnis, R. S., & McGinnis, E. W. (2022) · Sensors · doi:10.3390/s22124576 · Cited by 9 · see citing works

Validation status of cognitive digital assessments by the FDA BEST framework and context of use in preclinical AD studies: A systematic review

Porta-Mas, C., Grau-Rivera, O., Gispert, J., Blasco, G. S., & Sánchez-Benavides, G. (2025) · Alzheimer's & Dementia · doi:10.1002/alz.70753 · Cited by 9 · see citing works

A framework of digital biomarkers for neurodegenerative diseases

Nerrise, F., Schütz, N., Zhao, Q., Gould, C. E., Milstein, A. S., Schulman, K. A., Henderson, V. W., Landay, J. A., Fei-Fei, L., Lin, F. V., et al. (2026) · Nature Reviews Bioengineering · doi:10.1038/s44222-026-00433-7 · Cited by 8 · see citing works

Digital measures of respiratory and upper limb function in spinal muscular atrophy: design, feasibility, reliability, and preliminary validity of a smartphone sensor-based assessment suite

Perumal, T. M., Wolf, D., Berchtold, D., Pointeau, G., Zhang, Y., Cheng, W., Lipsmeier, F., Sprengel, J., Czech, C., Chiriboga, C. A., et al. (2023) · Neuromuscular Disorders · doi:10.1016/j.nmd.2023.07.008 · Cited by 7 · see citing works

Using wearable sensors and machine learning to assess upper limb function in Huntington’s disease

Nunes, A. S., Potter, İ. Y., Mishra, R. K., Casado, J., Dana, N., Geronimo, A. M., Tarolli, C. G., Schneider, R. B., Dorsey, E. R., Adams, J., et al. (2025) · Communications Medicine · doi:10.1038/s43856-025-00770-5 · Cited by 7 · see citing works

Assessment of non-directed computer-use behaviours in the home can indicate early cognitive impairment: A proof of principle longitudinal study

Stringer, G., Couth, S., Heuvelman, H., Bull, C., Gledson, A., Keane, J. A., Rayson, P., Sutcliffe, A., Sawyer, P., Zeng, X., et al. (2022) · Aging & Mental Health · doi:10.1080/13607863.2022.2036946 · Cited by 7 · see citing works

PhoneMD: Learning to Diagnose Parkinson’s Disease from Smartphone Data

Schwab, P., & Karlen, W. (2019) · Proceedings of the AAAI Conference on Artificial Intelligence · doi:10.1609/aaai.v33i01.33011118 · Cited by 7 · see citing works

Applications of machine learning and multimodal integration for the early diagnosis of neurodegenerative diseases (Review)

Velmurugan, S., Waheeda, S., Kulanthaivel, L., & Subbaraj, G. K. (2025) · World Academy of Sciences Journal · doi:10.3892/wasj.2025.403 · Cited by 6 · see citing works

Integrating Rehabilomics into the Multi-Omics Approach in the Management of Multiple Sclerosis: The Way for Precision Medicine?

Bonnechère, B. (2022) · Genes · doi:10.3390/genes14010063 · Cited by 6 · see citing works

Smartphone-Based Assessment of Mobility and Manual Dexterity in Adult People with Spinal Muscular Atrophy

Arteaga-Bracho, E. E., Cosne, G., Kanzler, C. M., Karatsidis, A., Mazzà, C., Penalver-Andres, J. A., Zhu, C., Shen, C., Erb, M. K., Freigang, M., et al. (2024) · Journal of Neuromuscular Diseases · doi:10.3233/jnd-240004 · Cited by 6 · see citing works

Acceptability of digital health technologies in early Parkinson's disease: lessons from WATCH-PD

Kangarloo, T., Latzman, R. D., Adams, J., Dorsey, R., Kostrzebski, M. A., Severson, J., Anderson, D. G., Horak, F. B., Stephenson, D. T., & Cosman, J. D. (2024) · Frontiers in Digital Health · doi:10.3389/fdgth.2024.1435693 · Cited by 6 · see citing works

Acceptability, validity and responsiveness of inertial measurement units for assessing motor recovery after gene therapy in infants with early onset spinal muscular atrophy: a prospective cohort study

Barrois, R., Tervil, B., Cacioppo, M., Barnérias, C., Deladrière, E., Leloup-Germa, V., Hervé, A., Oudre, L., Ricard, D., Vidal, P. P., et al. (2024) · Journal of NeuroEngineering and Rehabilitation · doi:10.1186/s12984-024-01477-9 · Cited by 6 · see citing works

Differential cognitive functioning in the digital clock drawing test in AD-MCI and PD-MCI populations

Wang, C., Li, K., Huang, S., Liu, J., Li, S., Tu, Y., Wang, B., Zhang, P., Luo, Y., & Chen, T. (2025) · Frontiers in Neuroscience · doi:10.3389/fnins.2025.1558448 · Cited by 6 · see citing works

A new approach to digitized cognitive monitoring: validity of the SelfCog in Huntington’s disease

Lunven, M., Dominguez, K. H., Youssov, K., Bagnou, J. H., Fliss, R., Vandendriessche, H., Bapst, B., Morgado, G., Rémy, P., Schubert, R., et al. (2023) · Brain Communications · doi:10.1093/braincomms/fcad043 · Cited by 6 · see citing works

Oportunidad en la salud digital: una respuesta al control de las demencias

Godoy, J. A., Carola Ríos, L., Venegas, P., Carolina López, R., Álvarez, J. L., Labbé, T., Camila Ramírez, M., & Ríos, J. A. (2020) · Revista médica de Chile · doi:10.4067/s0034-98872020000701018 · Cited by 6 · see citing works

Determination of Saccade Latency Distributions using Video Recordings from Consumer-grade Devices

Saavedra-Peña, G., Lai, H.-Y., Sze, V., & Heldt, T. (2018) · Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) · doi:10.1109/embc.2018.8512281 · Cited by 6 · see citing works

Voice as a digital biomarker in schizophrenia: a scoping review protocol on the application of artificial intelligence

Amir‐Behghadami, M., Farhang, S., Samad‐Soltani, T., & Lotfi, A. (2025) · BMJ Open · doi:10.1136/bmjopen-2025-099475 · Cited by 5 · see citing works

Detection Performance Regarding Sleep Apnea-Hypopnea Episodes with Fuzzy Logic Fusion on Single-Channel Airflow Indexes

Wu, M., Huang, W., Chang, K.-M., Lin, P., Kuo, C.-H., Hsu, C.-W., & Shen, T. (2020) · Applied Sciences · doi:10.3390/app10051868 · Cited by 5 · see citing works

Biases 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

Exploring Asymmetric Fine Motor Impairment Trends in Early Parkinson's Disease via Keystroke Typing

Holmes, A. A., Matarazzo, M., Mondesire-Crump, I., Katz, E. R., Mahajan, R., & Arroyo‐Gallego, T. (2023) · Movement Disorders Clinical Practice · doi:10.1002/mdc3.13864 · Cited by 5 · see citing works

Connecting real-world digital mobility assessment to clinical outcomes for regulatory and clinical endorsement – the Mobilise-D study protocolPreprint

Mikolaizak, A. S., Rochester, L., Maetzler, W., Sharrack, B., Demeyer, H., Mazzà, C., Caulfield, B., García‐Aymerich, J., Vereijken, B., Arnera, V., et al. (2022) · medRxiv · doi:10.1101/2022.05.25.22275598 · Cited by 5 · see citing works

Feature Analysis of the Vowel [a:] in Individuals With Chronic Obstructive Pulmonary Disease and Healthy Controls

Idrisoglu, A., Dallora, A. L., Cheddad, A., Anderberg, P., Whitling, S., Jakobsson, A., & Berglund, J. S. (2025) · Journal of Voice · doi:10.1016/j.jvoice.2025.10.013 · Cited by 4 · see citing works

A systematic exploration of digital biomarkers for the detection of depressive episodes in bipolar disorder

Halabi, R., Mulsant, B. H., Tolend, M., Blumberger, D. M., DeShaw, A., Hintze, A., Gonzalez‐Torres, C., Husain, M. I., Kim, H. K., O’Donovan, C., et al. (2026) · npj Mental Health Research · doi:10.1038/s44184-026-00195-5 · Cited by 4 · see citing works

Digital Biomarkers for Neurodegenerative Disease

Erickson, C. M., Wexler, A., & Largent, E. A. (2025) · JAMA Neurology · doi:10.1001/jamaneurol.2024.3533 · Cited by 19 · see citing works

Development of Neurodegenerative Disease Diagnosis and Monitoring from Traditional to Digital Biomarkers

Song, J., Cho, E., Lee, H., Lee, S., Kim, S., & Kim, J. (2025) · Biosensors · doi:10.3390/bios15020102 · Cited by 37 · see citing works

Evolution of the digital biomarker ecosystem

Wright, J. M., Regele, O. B., Kourtis, L. C., Pszenny, S. M., Sirkar, R., Kovalchick, C., & Jones, G. B. (2017) · Digital Medicine · doi:10.4103/digm.digm_35_17 · Cited by 17 · see citing works

Digital Biomarkers in Brain Health and Neurodegenerative Disorders: Current Evidence, Clinical Applications, and Future Directions

Koregaonkar, Y. (2026) · Zenodo (CERN European Organization for Nuclear Research) · doi:10.5281/zenodo.18185008

Clinical use of biomarkers for neurodegenerative disorders

(2014) · Frontiers research topics · doi:10.3389/978-2-88919-400-1