STOP: A Smartphone-based Game for Parkinson's Disease Medication Adherence

被引:3
|
作者
Kan, Valerii [1 ]
Rajanen, Dorina [2 ]
Asare, Kennedy Opoku [1 ]
Ferre, Nzil [1 ]
机构
[1] Univ Oulu, Ctr Ubiquitous Comp, Oulu, Finland
[2] Univ Oulu, Interact Res Unit, Oulu, Finland
来源
PROCEEDINGS OF THE 2018 ACM INTERNATIONAL JOINT CONFERENCE ON PERVASIVE AND UBIQUITOUS COMPUTING AND PROCEEDINGS OF THE 2018 ACM INTERNATIONAL SYMPOSIUM ON WEARABLE COMPUTERS (UBICOMP/ISWC'18 ADJUNCT) | 2018年
基金
芬兰科学院;
关键词
Parkinson's disease; smartphone; gamification; instrumentation;
D O I
10.1145/3267305.3267598
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Parkinson's disease (PD) is a second most common neurological disorder that affects up to 10 million people worldwide. It has an evolving nature and the symptoms may vary from patient to patient. Thus, to increase the effectiveness of PD treatment, it is necessary a personalized medication plan. Currently, PD patients undergo symptom observation on semiannual clinical visits. This work aims at the development of a new way of observation via smartphones, while at the same time offering the PD patient a tool to better understand his medication needs. Our mobile application leverages smartphone's inbuilt sensors in order to keep track of subject's medication adherence throughout the day, taking shape as a short-term accelerometer-based game played several times a day, and allows PD patients to record when they took medication. The combination of collected datasets can be used in further studies in order to estimate the changes in PD severity and medication effectiveness over time.
引用
收藏
页码:373 / 376
页数:4
相关论文
共 50 条
  • [21] The STEPWISE study: study protocol for a smartphone-based exercise solution for people with Parkinson's Disease (randomized controlled trial)
    Schootemeijer, Sabine
    de Vries, Nienke M.
    Macklin, Eric A.
    Roes, Kit C. B.
    Joosten, Hilde
    Omberg, Larsson
    Ascherio, Alberto
    Schwarzschild, Michael A.
    Bloem, Bastiaan R.
    BMC NEUROLOGY, 2023, 23 (01)
  • [22] Assessing motor skills in Parkinson's Disease using smartphone-based video analysis and machine learning
    Stergioulas, Andreas
    Dias, Sofia Balula
    Alves, Beatriz
    al Hussein, Ghada
    Bostantjopoulou, Sevasti
    Katsarou, Zoe
    Dagklis, Ioannis
    Grammalidis, Nikos
    Dimitropoulos, Kosmas
    17TH ACM INTERNATIONAL CONFERENCE ON PERVASIVE TECHNOLOGIES RELATED TO ASSISTIVE ENVIRONMENTS, PETRA 2024, 2024, : 562 - 568
  • [23] Simple Smartphone-Based Assessment of Gait Characteristics in Parkinson Disease: Validation Study
    Su, Dongning
    Liu, Zhu
    Jiang, Xin
    Zhang, Fangzhao
    Yu, Wanting
    Ma, Huizi
    Wang, Chunxue
    Wang, Zhan
    Wang, Xuemei
    Hu, Wanli
    Manor, Brad
    Feng, Tao
    Zhou, Junhong
    JMIR MHEALTH AND UHEALTH, 2021, 9 (02):
  • [24] Smartphone-Based Estimation of Item 3.8 of the MDS-UPDRS-III for Assessing Leg Agility in People With Parkinson's Disease
    Borzi, Luigi
    Varrecchia, Marilena
    Sibille, Stefano
    Olmo, Gabriella
    Artusi, Carlo Alberto
    Fabbri, Margherita
    Rizzone, Mario Giorgio
    Romagnolo, Alberto
    Zibetti, Maurizio
    Lopiano, Leonardo
    IEEE OPEN JOURNAL OF ENGINEERING IN MEDICINE AND BIOLOGY, 2020, 1 : 140 - 147
  • [25] Use of Smartphone-Based Video Directly Observed Therapy to Increase Tuberculosis Medication Adherence: An Interventional Study
    Al Daajani, Manal M.
    Alsahafi, Abdullah J.
    Algarni, Abdullah M.
    Moawwad, Abdulhamed L.
    Osman, Ahmed A.
    Algaali, Khalid Y. A.
    Abdalaziz, Mohammed
    Halwani, Muhammad A.
    Aldajani, Shrooq M.
    Mohammed, Nazik M. H.
    Alshamrani, Heassah S.
    Alshahrani, Mohammed N.
    Albostani, Ghadah M.
    Alshammari, Naif G.
    Alzahrani, Rami S.
    Alsomali, Saadiya O.
    Assiri, Ibrahim
    GALEN MEDICAL JOURNAL, 2023, 12
  • [26] Challenges and strategies of medication adherence in Parkinson's disease: A qualitative study
    Shin, Ju Young
    Habermann, Barbara
    Pretzer-Aboff, Ingrid
    GERIATRIC NURSING, 2015, 36 (03) : 192 - 196
  • [27] Smartphone-Based Detection of Early Parkinson's Disease With Tapping Records and a Multimodal-Multiscale Ensemble Network
    He, Tongyue
    Chen, Junxin
    Chen, Yongyong
    IEEE SENSORS JOURNAL, 2024, 24 (20) : 33207 - 33216
  • [28] Assessment of Health-Related Quality of Life between People with Parkinson's Disease and Non-Parkinson's: Using Data Drawn from the '100 for Parkinson's' Smartphone-Based Prospective Study
    Fan, Xiaojing
    Wang, Duolao
    Hellman, Bruce
    Janssen, Mathieu F.
    Bakker, Gerben
    Coghlan, Rupert
    Hursey, Amelia
    Matthews, Helen
    Whetstone, Ian
    INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH, 2018, 15 (11)
  • [29] Cuing Prospective Memory With Smartphone-Based Calendars in Alzheimer's Disease
    El Haj, Mohamad
    Moustafa, Ahmed A.
    Gallouj, Karim
    Allain, Philippe
    ARCHIVES OF CLINICAL NEUROPSYCHOLOGY, 2021, 36 (03) : 316 - 321
  • [30] Evaluation of Smartphone-Based Testing to Generate Exploratory Outcome Measures in a Phase 1 Parkinson's Disease Clinical Trial
    Lipsmeier, Florian
    Taylor, Kirsten I.
    Kilchenmann, Timothy
    Wolf, Detlef
    Scotland, Alf
    Schjodt-Eriksen, Jens
    Cheng, Wei-Yi
    Fernandez-Garcia, Ignacio
    Siebourg-Polster, Juliane
    Jin, Liping
    Soto, Jay
    Verselis, Lynne
    Boess, Frank
    Koller, Martin
    Grundman, Michael
    Monsch, Andreas U.
    Postuma, Ronald B.
    Ghosh, Anirvan
    Kremer, Thomas
    Czech, Christian
    Gossens, Christian
    Lindemann, Michael
    MOVEMENT DISORDERS, 2018, 33 (08) : 1287 - 1297