The mPower study, Parkinson disease mobile data collected using ResearchKit

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Items 101–200 of 630

1. Psilocybin microdosers demonstrate greater observed improvements in mood and mental health at one month relative to non-microdosing controls
   Joseph M. Rootman, Maggie Kamila Kiraga, Pamela Kryskow, Kalin Harvey, Paul E. Stamets, Eesmyal Santos-Brault, Kim P. C. Kuypers, Zach Walsh · 2022 · Scientific Reports
2. Possibilities, Problems, and Perspectives of Data Collection by Mobile Apps in Longitudinal Epidemiological Studies: Scoping Review
   Florian Fischer, Sina Kleen · 2020 · Journal of Medical Internet Research
3. Recruitment and Ongoing Engagement in a UK Smartphone Study Examining the Association Between Weather and Pain: Cohort Study
   Katie L. Druce, John McBeth, Sabine N van der Veer, David Selby, Bertie Vidgen, Konstantinos Georgatzis, Bruce Hellman, Rashmi Lakshminarayana, Afiqul Chowdhury, David M. Schultz et al. · 2017 · JMIR mhealth and uhealth
4. Objectively Monitoring Amyotrophic Lateral Sclerosis Patient Symptoms During Clinical Trials With Sensors: Observational Study
   Luis Garcia‐Gancedo, Madeline L Kelly, Arseniy Lavrov, Jim Parr, R G Hart, Rachael Marsden, Martin R. Turner, Kevin Talbot, Theresa Chiwera, Christopher E. Shaw et al. · 2019 · JMIR mhealth and uhealth
5. Big data in Parkinson’s disease: using smartphones to remotely detect longitudinal disease phenotypes
   John Prince, Siddharth Arora, Maarten De Vos · 2018 · Physiological Measurement
6. The Healthy Pregnancy Research Program: transforming pregnancy research through a ResearchKit app
   Jennifer M. Radin, Steven R. Steinhubl, Andrew I. Su, Hansa Bhargava, Benjamin M. Greenberg, Brian M. Bot, Megan J. Doerr, Eric J. Topol · 2018 · npj Digital Medicine
7. Machine learning- and statistical-based voice analysis of Parkinson’s disease patients: A survey
   Federica Amato, Giovanni Saggio, Valerio Cesarini, Gabriella Olmo, Giovanni Costantini · 2023 · Expert Systems with Applications
8. Co-designing smart home technology with people with dementia or Parkinson's disease
   Aikaterini Bourazeri, Simone Stumpf · 2018 · Nordic Conference on Human-Computer Interaction
9. Digital Progression Biomarkers as Novel Endpoints in Clinical Trials: A Multistakeholder Perspective
   Diane T. Stephenson, Reham Badawy, Soania Mathur, Maria Begona Tome, Lynn Rochester · 2021 · Journal of Parkinson s Disease
10. Clinical validation of smartphone-based activity tracking in peripheral artery disease patients
    Raheel Ata, Neil Gandhi, Hannah Rasmussen, Osama El-Gabalawy, Santiago Gutierrez, Alizeh Ahmad, Siddharth Suresh, Roshini Ravi, Kara A. Rothenberg, Oliver O. Aalami · 2018 · npj Digital Medicine
11. Remote Assessment of Parkinson’s Disease Symptom Severity Using the Simulated Cellular Mobile Telephone Network
    Athanasios Tsanas, Max A. Little, Lorraine O. Ramig · 2021 · IEEE Access
12. A Long Way to Go: Patient Perspectives on Digital Health for Parkinson’s Disease
    Sara S. Riggare, Jon Stamford, Maria Hägglund · 2021 · Journal of Parkinson s Disease
13. Digital Technology and Mobile Health in Behavioral Migraine Therapy: a Narrative Review
    Anker Stubberud, Mattias Linde · 2018 · Current Pain and Headache Reports
14. A Deep Learning Framework for the Remote Detection of Parkinson’S Disease Using Smart-Phone Sensor Data
    John Prince, Maarten De Vos · 2018 · Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)
15. Depression Screening from Voice Samples of Patients Affected by Parkinson’s Disease
    Yasin Özkanca, Miraç Göksu Öztürk, Merve Nur Ekmekci, David C. Atkins, Cenk Demiroğlu, Reza Hosseini Ghomi · 2019 · Digital Biomarkers
16. PhoneMD: Learning to Diagnose Parkinson’s Disease from Smartphone Data
    Patrick Schwab, Walter Karlen · 2019 · Proceedings of the AAAI Conference on Artificial Intelligence
17. Feasibility and Utility of mHealth for the Remote Monitoring of Parkinson Disease: Ancillary Study of the PD_manager Randomized Controlled Trial
    Dimitrios A. Gatsios, Angelo Antonini, Giovanni Gentile, Andrea Marcante, Clelia Pellicano, Lucia Macchiusi, Francesca Assogna, Gianfranco Spalletta, Heather Gage, Morro Touray et al. · 2020 · JMIR mhealth and uhealth
18. Evaluation, Acceptance, and Qualification of Digital Measures: From Proof of Concept to Endpoint
    Jennifer C. Goldsack, Ariel V. Dowling, David Samuelson, Bray Patrick‐Lake, Ieuan Clay · 2021 · Digital Biomarkers
19. The asthma mobile health study, smartphone data collected using ResearchKit
    Yu‐Feng Yvonne Chan, Brian M. Bot, Micol Zweig, Nicole L. Tignor, Weiping Ma, Christine Suver, Rafhael Cedeno, Erick R. Scott, Steven Gregory Hershman, Eric E. Schadt et al. · 2018 · Scientific Data
20. Beyond smartphones and sensors: choosing appropriate statistical methods for the analysis of longitudinal data
    Ian Barnett, John Blake Torous, Patrick C. Staples, Matcheri S. Keshavan, Jukka-Pekka “JP” Onnela · 2018 · Journal of the American Medical Informatics Association
21. Usage Patterns of GlucoNote, a Self-Management Smartphone App, Based on ResearchKit for Patients With Type 2 Diabetes and Prediabetes
    Satoko Yamaguchi, Kayo Waki, Yasuhito Nannya, Masaomi Nangaku, Takashi Kadowaki, Kazuhiko Ohe · 2019 · JMIR mhealth and uhealth
22. Parkinson’s disease diagnosis using deep learning: A bibliometric analysis and literature review
    Rabab Ali Abumalloh, Mehrbakhsh Nilashi, Sarminah Samad, Hossein Ahmadi, Abdullah Alghamdi, Mesfer Alrizq, Sultan Sughair AlYami · 2024 · Ageing Research Reviews
23. A smartphone-based system to quantify dexterity in Parkinson's disease patients
    Somayeh Aghanavesi, Dag Nyholm, Marina Senek, Filip Bergquist, Mevludin Memedi · 2017 · Informatics in Medicine Unlocked
24. Development of Novel, Value-Based, Digital Endpoints for Clinical Trials: A Structured Approach Toward Fit-for-Purpose Validation
    Matthijs D. Kruizinga, Frederik E. Stuurman, Vasileios Exadaktylos, Robert Jan Doll, Diane T. Stephenson, Geert Jan Groeneveld, Gertjan J. A. Driessen, Adam F. Cohen · 2020 · Pharmacological Reviews
25. Present and Future of Digital Health in Diabetes and Metabolic Disease
    Rhee, Sang Youl, Kim, Chiweon, Shin, Dong Wook, Steinhubl, Steven R. · 2020 · Diabetes & Metabolism Journal
26. mHealth Technologies Towards Parkinson's Disease Detection and Monitoring in Daily Life: A Comprehensive Review
    Hanbin Zhang, Chen Song, Aditya Singh Rathore, Ming-Chun Huang, Yuan Zhang, Wenyao Xu · 2020 · IEEE Reviews in Biomedical Engineering
27. Learning endometriosis phenotypes from patient-generated data
    Iñigo Urteaga, Mollie M. McKillop, Noémie Elhadad · 2020 · npj Digital Medicine
28. Motor Impairment Estimates via Touchscreen Typing Dynamics Toward Parkinson's Disease Detection From Data Harvested In-the-Wild
    Dimitrios Iakovakis, Stelios Hadjidimitriou, Vasileios S. Charisis, Sevasti Bostantjopoulou, Zoe Katsarou, Lisa Klingelhoefer, Heinz Reichmann, Sofia B. Dias, José Alves Diniz, Dhaval Trivedi et al. · 2018 · Frontiers in ICT
29. Detecting Parkinson’s Disease from Wrist-Worn Accelerometry in the U.K. Biobank
    James R. Williamson, Brian A. Telfer, Riley Mullany, Karl E. Friedl · 2021 · Sensors
30. MyCap: a flexible and configurable platform for mobilizing the participant voice
    Paul A. Harris, Jonathan A. Swafford, Emily Sheffer Serdoz, Jessica Eidenmuller, Giovanni Delacqua, Vaishali Jagtap, Robert J. Taylor, Alexander H. Gelbard, Alex Cheng, Stephany N. Duda · 2022 · JAMIA Open
31. PDVocal
    Hanbin Zhang, Chen Song, Aosen Wang, Chenhan Xu, Dongmei Li, Wenyao Xu · 2019 · ACM Annual International Conference on Mobile Computing and Networking (MobiCom)
32. New medical big data for P4 medicine on allergic conjunctivitis
    Takenori Inomata, Jaemyoung Sung, Masahiro Nakamura, Kumiko Fujisawa, Kaori Muto, Nobuyuki Ebihara, Masao Iwagami, Masahiro Nakamura, Kenta Fujio, Yuichi Okumura et al. · 2020 · Allergology International
33. Demographic Imbalances Resulting From the Bring-Your-Own-Device Study Design
    Peter Jaeho Cho, Jaehan Yi, Ethan Ho, Md Mobashir Hasan Shandhi, Yen Dinh, Aneesh Patil, Leatrice Martin, Geetika Singh, Brinnae Bent, Geoffrey S. Ginsburg et al. · 2021 · JMIR mhealth and uhealth
34. Precision Medicine in Parkinson’s Disease – Exploring Patient-Initiated Self-Tracking
    Sara S. Riggare, Maria Hägglund · 2018 · Journal of Parkinson s Disease
35. Machine learning-based motor assessment of Parkinson’s disease using postural sway, gait and lifestyle features on crowdsourced smartphone data
    Hamza Abujrida, Emmanuel Agu, Kaveh Pahlavan · 2019 · Biomedical Physics & Engineering Express
36. Parkinson’s disease detection from 20-step walking tests using inertial sensors of a smartphone: Machine learning approach based on an observational case-control study
    Milla Juutinen, Cassia Wang, Justin Xi Zhu, Juan Haladjian, Jari Ruokolainen, Juha Puustinen, Antti T. Vehkaoja · 2020 · PLoS ONE
37. Smartphone-Based Neuropsychological Assessment in Parkinson’s Disease: Feasibility, Validity, and Contextually Driven Variability in Cognition
    Emma L. Weizenbaum, Daniel Fulford, John Blake Torous, Emma Pinsky, Vijaya B. Kolachalama, Alice Cronin‐Golomb · 2021 · Journal of the International Neuropsychological Society
38. Recent use of deep learning techniques in clinical applications based on gait: a survey
    Yume Matsushita, Dinh Tuan Tran, Hirotake Yamazoe, Joo‐Ho Lee · 2021 · Journal of Computational Design and Engineering
39. Evaluation of PDQ-8 and its relationship with PDQ-39 in China: a three-year longitudinal study
    Kui Chen, Yujie Yang, Fengtao Liu, Dake Li, Lu-Lu Bu, Kehu Yang, Ying Wang, Bo Shen, Rong‐Yuan Guan, Jie Song et al. · 2017 · Health and Quality of Life Outcomes
40. Screening of Parkinsonian subtle fine-motor impairment from touchscreen typing via deep learning
    Dimitrios Iakovakis, К. Ray Chaudhuri, Lisa Klingelhoefer, Sevasti Bostantjopoulou, Zoe Katsarou, Dhaval Trivedi, Heinz Reichmann, Stelios Hadjidimitriou, Vasileios S. Charisis, Leontios J. Hadjileontiadis · 2020 · Scientific Reports
41. Using Medical Big Data to Develop Personalized Medicine for Dry Eye Disease
    Takenori Inomata, Jaemyoung Sung, Masahiro Nakamura, Masao Iwagami, Yuichi Okumura, Nanami Iwata, Akie Midorikawa‐Inomata, Keiichi Fujimoto, Atsuko Eguchi, Ken Nagino et al. · 2020 · Cornea
42. DeepVoice: A voiceprint-based mobile health framework for Parkinson's disease identification
    Hanbin Zhang, Aosen Wang, Dongmei Li, Wenyao Xu · 2018 · IEEE-EMBS International Conference on Biomedical and Health Informatics (BHI ...)
43. Dichotomies in the Development and Implementation of Digital Mental Health Tools
    John Blake Torous, Adam Haim · 2018 · Psychiatric Services
44. Accurate detection of cerebellar smooth pursuit eye movement abnormalities via mobile phone video and machine learning
    Zhuoqing Chang, Ziyu Chen, Christopher D. Stephen, Jeremy Dan Schmahmann, Hau‐Tieng Wu, Guillermo Sapiro, Anoopum S. Gupta · 2020 · Scientific Reports
45. A mobile-assisted voice condition analysis system for Parkinson’s disease: assessment of usability conditions
    Javier Carrón, Y. Campos‐Roca, Mario Madruga, Carlos Javier Pérez · 2021 · BioMedical Engineering OnLine
46. AI-driven precision diagnosis and treatment in Parkinson’s disease: a comprehensive review and experimental analysis
    Bhekisipho Twala · 2025 · Frontiers in Aging Neuroscience
47. Neuroinflammation — using big data to inform clinical practice
    Calliope Athena Dendrou, Gil McVean, Lars H. Fugger · 2016 · Nature Reviews Neurology
48. Identifying and Quantifying Neurological Disability via Smartphone
    Alexandra K. Boukhvalova, Emily Kowalczyk, Thomas Harris, Peter F. Kosa, Alison Wichman, Mary Sandford, Atif M. Memon, Bibiana Bielekova · 2018 · Frontiers in Neurology
49. Characterizing patient compliance over six months in remote digital trials of Parkinson’s and Huntington disease
    Shani Attias Cohen, Zeev Waks, Jordan J. Elm, Mark Forrest Gordon, Igor D. Grachev, Leehee Navon-Perry, Shai Fine, Iris Grossman, Spyridon Papapetropoulos, Juha‐Matti Savola · 2018 · BMC Medical Informatics and Decision Making
50. A Hybrid U-Lossian Deep Learning Network for Screening and Evaluating Parkinson’s Disease
    Rytis Maskeliūnas, Robertas Damaševičius, Audrius Kulikajevas, Evaldas Padervinskis, Kipras Pribuišis, Virgilijus Uloza · 2022 · Applied Sciences
51. Developing Smartphone-Based Objective Assessments of Physical Function in Rheumatoid Arthritis Patients: The PARADE Study
    Hamy, Valentin, Garcia-Gancedo, Luis, Pollard, Andrew, Myatt, Anniek, Liu, Jingshu, Howland, Andrew, Beineke, Philip, Quattrocchi, Emilia, Williams, Rachel, Crouthamel, Michelle · 2020 · Digital Biomarkers
52. Machine Learning Smart System for Parkinson Disease Classification Using the Voice as a Biomarker
    Ilias Tougui, Abdelilah Jilbab, Jamal El Mhamdi · 2022 · Healthcare Informatics Research
53. Leveraging Mobile Technology for Public Health Promotion: A Multidisciplinary Perspective
    Jennifer L. Hicks, Melissa A. Boswell, Tim Althoff, Alia Joy Crum, Joy P. Ku, James A. Landay, Paula M. L. Moya, Elizabeth L. Murnane, Michael P. Snyder, Abby C. King et al. · 2022 · Annual Review of Public Health
54. Computer vision and behavioral phenotyping: an autism case study
    Guillermo Sapiro, Jordan Hashemi, Géraldine Dawson · 2018 · Current Opinion in Biomedical Engineering
55. Digital Health Integration With Neuromodulation Therapies: The Future of Patient-Centric Innovation in Neuromodulation
    Yagna J. Pathak, Walter Greenleaf, Leo Verhagen Metman, Pieter Kubben, Sridevi V. Sarma, Brian Pepin, Douglas Lautner, Scott DeBates, Alexander M. Benison, Binesh Balasingh et al. · 2021 · Frontiers in Digital Health
56. Parkinson’s disease severity clustering based on tapping activity on mobile device
    Decho Surangsrirat, Panyawut Sri-iesaranusorn, Attawit Chaiyaroj, Peerapon Vateekul, Roongroj Bhidayasiri · 2022 · Scientific Reports
57. Data Representativeness in Accessibility Datasets: A Meta-Analysis
    Rie Kamikubo, Lining Wang, Crystal Marte, Amnah Mahmood, Hernisa Kacorri · 2022 · International ACM SIGACCESS Conference on Computers and Accessibility (ASSETS)
58. Leveraging mobile health applications for biomedical research and citizen science: a scoping review
    Hannah Schmitz, Carol L. Howe, David G. Armstrong, Vignesh Subbian · 2018 · Journal of the American Medical Informatics Association
59. What Can Gestures Tell?
    Feng Tian, Xiangmin Fan, Junjun Fan, Yi‐Cheng Zhu, Jing Gao, Dakuo Wang, Xiaojun Bi, Hongan Wang · 2019 · CHI Conference on Human Factors in Computing Systems
60. Smartphone Voice Calls Provide Early Biomarkers of Parkinsonism in Rapid Eye Movement Sleep Behavior Disorder
    Vojtěch Illner, Michal Novotný, Tomáš Kouba, Tereza Tykalová, Michal Šimek, Pavel Sovka, Jan Švihlík, Evžen Růžička, Karel Šonka, Petr Dušek et al. · 2024 · Movement Disorders
61. Smartphone applications to assess gait and postural control in people with multiple sclerosis: A systematic review
    Libak Abou, Ellyce Wong, Joseph Peters, Mauricette Sènan Dossou, Jacob J. Sosnoff, Laura A. Rice · 2021 · Multiple Sclerosis and Related Disorders
62. Smartphone-Based Digital Biomarkers for Parkinson’s Disease in a Remotely-Administered Setting
    María Goñi, Simon Bodo Eickhoff, Mehran Sahandi Far, Kaustubh R. Patil, Juergen Dukart · 2022 · IEEE Access
63. Telemedicine Use for Movement Disorders: A Global Survey
    Anhar Hassan, Earl Ray Dorsey, Christopher G. Goetz, Bastiaan R. Bloem, Mark Guttman, Caroline M. Tanner, Zoltan K. Mari, Alexander Y. Pantelyat, Nicholas B. Galifianakis, Jawad A. Bajwa et al. · 2018 · Telemedicine Journal and e-Health
64. Remote Digital Psychiatry for Mobile Mental Health Assessment and Therapy: MindLogger Platform Development Study
    Arno Klein, Jon C. Clucas, Anirudh Krishnakumar, Satrajit Ghosh, Wilhelm Van Auken, Benjamin Thonet, Ihor Sabram, Nino Acuna, Anisha Keshavan, Henry Rossiter et al. · 2021 · Journal of Medical Internet Research
65. Smartphones as new tools in the management and understanding of Parkinson’s disease
    Andrew Daniel Trister, Earl Ray Dorsey, Stephen Henry Friend · 2016 · npj Parkinson s Disease
66. Digital phenotyping and sensitive health data: Implications for data governance
    Ignacio Perez-Pozuelo, Dimitris Spathis, Jordan Gifford-Moore, Jessica Morley, Josh Cowls · 2021 · Journal of the American Medical Informatics Association
67. Wearable Sensor-Based Assessments for Remotely Screening Early-Stage Parkinson’s Disease
    Shane Johnson, Michalis Kantartjis, Joan Severson, Ray E. Dorsey, Jamie Adams, Tairmae Kangarloo, Melissa A. Kostrzebski, Allen Best, Michael Merickel, Dan Amato et al. · 2024 · Sensors
68. Apkinson: the Smartphone Application for Telemonitoring Parkinson’s Patients Through speech, Gait and Hands Movement
    Juan Rafael Orozco‐Arroyave, Juan Camilo Vásquez-Correa, Philipp Klumpp, Paula Andrea Pérez-Toro, Daniel Escobar-Grisales, Nils Roth, Cristian David Ríos-Urrego, Martin Strauss, Helber Andrés Carvajal-Castaño, Sebastian Peter Bayerl et al. · 2020 · Neurodegenerative Disease Management
69. The evolution of Big Data in neuroscience and neurology
    Laura Dipietro, Paola Gonzalez‐Mego, Ciro Ramos-Estébanez, Lauren H. Zukowski, Rahul Mikkilineni, Jarrett Rushmore, Timothy Wagner · 2023 · Journal Of Big Data
70. Augmented Reality Games as a New Class of Physical Activity Interventions? The Impact of Pokémon Go Use and Gaming Intensity on Physical Activity
    Michael Yuxuan Ni, Rex WH Hui, Tom K. Li, Anna H.M. Tam, L Y Lois Choy, Kitty K.W., Felix Cheung, Gabriel Matthew Leung · 2018 · Games for Health Journal
71. Toward IoRT Collaborative Digital Twin Technology Enabled Future Surgical Sector: Technical Innovations, Opportunities and Challenges
    Chetana Das, Anika Anis Mumu, Md. Firoj Ali, S. Sarker, S. Muyeen, Sajal Kumar Das, P. Das, M. Hasan, Z. Tasneem, Md. Manirul Islam et al. · 2022 · IEEE Access
72. Digital Phenotyping in Clinical Neurology
    Anoopum S. Gupta · 2022 · Seminars in Neurology
73. Biometric Digital Health Technology for Measuring Motor Function in Parkinson’s Disease: Results from a Feasibility and Patient Satisfaction Study
    Georgia Mitsi, Enrique Urrea‐Mendoza, Benjamin D. Wissel, Elena Barbopoulou, Alok Kumar Dwivedi, Ioannis G. Tsoulos, Athanassios Stavrakoudis, Alberto Javier Espay, Spyridon Papapetropoulos · 2017 · Frontiers in Neurology
74. Quadruple Decision Making for Parkinson’s Disease Patients: Combining Expert Opinion, Patient Preferences, Scientific Evidence, and Big Data Approaches to Reach Precision Medicine
    Lieneke van den Heuvel, Ray Dorsey, Barbara Prainsack, Bart Post, Anne Margarethe Stiggelbout, Marjan J. Meinders, Bastiaan R. Bloem · 2019 · Journal of Parkinson s Disease
75. Parkinson Data Analysis and Prediction System Using Multi-Variant Stacked Auto Encoder
    Gayathri Nagasubramanian, S. Muthuramalingam, Fadi M. Al-Turjman, Georgios Tsaramirsis · 2020 · IEEE Access
76. Design of a virtual longitudinal observational study in Parkinson’s disease (AT‐HOME PD)
    Ruth B. Schneider, Larsson Omberg, Eric A. Macklin, Margaret Daeschler, Lauren Bataille, Shalini Anthwal, Taylor L. Myers, Elizabeth Baloga, Sidney Duquette, Phil Snyder et al. · 2020 · Annals of Clinical and Translational Neurology
77. Applying a Digital Health Checklist and Readability Tools to Improve Informed Consent for Digital Health Research
    Camille Nebeker, Maryam Gholami, Daniah Kareem, Emily Kim · 2021 · Frontiers in Digital Health
78. Heterogeneous digital biomarker integration out-performs patient self-reports in predicting Parkinson’s disease
    Kaiwen Deng, Yueming Li, Hanrui Zhang, Jian Wang, Roger L. Albin, Yuanfang Guan · 2022 · Communications Biology
79. DiaTrend: A dataset from advanced diabetes technology to enable development of novel analytic solutions
    Temiloluwa Prioleau, Abigail Bartolome, Richard J. Comi, Catherine Stanger · 2023 · Scientific Data
80. The role of artificial intelligence in the application of the integrated electronic health records and patient-generated health data
    Jiancheng Ye, Jiarui Hai, Jiacheng Song, Zidan Wang · 2024 · medRxiv
81. Digital Health Technologies in Patient Experience Literature: A Scoping Review and Future Outlook for Sustainable Digital Health Interventions
    Arif Aytekin, Hale Alan, Hüsne Demirel, Neslihan Onur, Ayşen Yalman, Tuba LİVBERBER, Fatma Yiğit Açıkgöz · 2025 · Sustainability
82. Big data, artificial intelligence, and cardiovascular precision medicine
    Chayakrit Krittanawong, Kipp W. Johnson, Steven Gregory Hershman, W.H. Wilson Tang · 2018 · Expert Review of Precision Medicine and Drug Development
83. Early Parkinson’s Disease Detection via Touchscreen Typing Analysis using Convolutional Neural Networks
    Dimitrios Iakovakis, José Alves Diniz, Dhaval Trivedi, К. Ray Chaudhuri, Leontios J. Hadjileontiadis, Stelios Hadjidimitriou, Vasileios S. Charisis, Sevasti Bostanjopoulou, Zoe Katsarou, Lisa Klingelhoefer et al. · 2019 · Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)
84. Exploring racial and gender disparities in voice biometrics
    Xingyu Chen, Zhengxiong Li, Srirangaraj Setlur, Wenyao Xu · 2022 · Scientific Reports
85. Regulatory-accepted drug development tools are needed to accelerate innovative CNS disease treatments
    Stephen P. Arnerić, Volker D. Kern, Diane T. Stephenson · 2018 · Biochemical Pharmacology
86. A multimodal dataset of real world mobility activities in Parkinson’s disease
    Catherine Morgan, Emma L. Tonkin, Alessandro Masullo, Ferdian Jovan, Arindam Sikdar, Pushpajit Khaire, Majid Mirmehdi, Ryan McConville, Gregory J. L. Tourte, Alan L. Whone et al. · 2023 · Scientific Data
87. An Analytics Platform to Evaluate Effective Engagement With Pediatric Mobile Health Apps: Design, Development, and Formative Evaluation
    Pham, Quynh, Graham, Gary, Lalloo, Chitra, Morita, Plinio P, Seto, Emily, Stinson, Jennifer N, Cafazzo, Joseph A · 2018 · JMIR mHealth and uHealth
88. A nationwide observational study of locomotive syndrome in Japan using the ResearchKit: The Locomonitor study
    Yusuke Yoshimura, Muneaki Ishijima, Masayoshi Ishibashi, Liz Liu, Eri Arikawa‐Hirasawa, Shuichi Machida, Hisashi Naıto, Chieko Hamada, Eiki Kominami · 2019 · Journal of Orthopaedic Science
89. The CloudUPDRS smartphone software in Parkinson’s study: cross-validation against blinded human raters
    Ashwani Jha, Elisa Menozzi, Rebecca Oyekan, Anna Latorre, Eoin Mulroy, Sebastian R. Schreglmann, Cosmin Stamate, Ioannis Daskalopoulos, Stefan Küppers, Marco U. Luchini et al. · 2020 · npj Parkinson s Disease
90. Exercise-Induced Neuroplasticity: Adaptive Mechanisms and Preventive Potential in Neurodegenerative Disorders
    Masab A. Mansoor, Andrew Ibrahim, Ali Hamide, Tyler Tran, Ethan Candreva, Jad Baltaji · 2025 · Physiologia
91. PPD ACT: an app-based genetic study of postpartum depression
    Jerry Guintivano, Holly Krohn, Carol Lewis, Enda M. Byrne, Anjali K. Henders, Alexander Ploner, Katherine M. Kirk, Nicholas G. Martin, Jeannette Milgrom, Naomi R. Wray et al. · 2018 · Translational Psychiatry
92. Automatic quality control and enhancement for voice-based remote Parkinson’s disease detection
    Amir Hossein Poorjam, Mathew Shaji Kavalekalam, Liming Shi, Yordan P. Raykov, Jesper Rindom Jensen, Max A. Little, Mads Græsbøll Christensen · 2020 · Speech Communication
93. Learning Bias-Invariant Representation by Cross-Sample Mutual Information Minimization
    Wei Zhu, Haitian Zheng, Haofu Liao, Weijian Li, Jiebo Luo · 2021 · IEEE/CVF International Conference on Computer Vision (ICCV)
94. Exploring Test-Retest Reliability and Longitudinal Stability of Digital Biomarkers for Parkinson Disease in the m-Power Data Set: Cohort Study
    Mehran Sahandi Far, Simon Bodo Eickhoff, María Goñi, Juergen Dukart · 2021 · Journal of Medical Internet Research
95. Developing a Transparent, Participant-Navigated Electronic Informed Consent for Mobile-Mediated Research
    Megan J. Doerr, Christine Suver, JOHN T. WILBANKS · 2016 · SSRN Electronic Journal
96. NeuroVoz: a Castillian Spanish corpus of parkinsonian speech
    Janaína Mendes-Laureano, Jorge A. Gómez-García, Alejandro Guerrero-López, Elisa Luque‐Buzo, Julián D. Arias-Londoño, Francisco Grandas, Juan Ignacio Godino-Llorente · 2024 · Scientific Data
97. Identifying and characterising sources of variability in digital outcome measures in Parkinson’s disease
    Roussos, George, Herrero, Teresa Ruiz, Hill, Derek L., Dowling, Ariel V., L. T. M. Müller, Martijn, Evers, Luc J. W., Burton, Jackson, Derungs, Adrian, Fisher, Katherine, Kilambi, Krishna Praneeth et al. · 2022 · npj Digital Medicine
98. “Back on Track”: A Mobile App Observational Study Using Apple’s ResearchKit Framework
    Martin Zens, Peter Woias, Norbert Paul Suedkamp, Philipp Niemeyer · 2017 · JMIR mhealth and uhealth
99. Pre-trained convolutional neural networks identify Parkinson’s disease from spectrogram images of voice samples
    Yasir Rahmatallah, Aaron S. Kemp, Anu Iyer, Lakshmi Pillai, Linda J. Larson‐Prior, Tuhin Virmani, Fred Prior · 2025 · Scientific Reports
100. Smartphone Level Test Measures Disability in Several Neurological Domains for Patients With Multiple Sclerosis
     Alexandra K. Boukhvalova, Olivia Fan, Ann Marie Weideman, Thomas Harris, Emily Kowalczyk, Linh Pham, Peter F. Kosa, Bibiana Bielekova · 2019 · Frontiers in Neurology