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Combined fine-motor tests and self-assessments for remote detection of motor fluctuations
Dalarna University, School of Technology and Business Studies, Computer Engineering. Örebro University.ORCID iD: 0000-0002-2372-4226
Neuroscience, Neurology, Uppsala University.
Dalarna University, School of Technology and Business Studies, Computer Engineering.ORCID iD: 0000-0003-0403-338X
2013 (English)In: Recent Patents on Biomedial Engineering, ISSN 1874-7647, Vol. 6, no 2, 127-135 p.Article in journal (Refereed) Published
Abstract [en]

A major problem with the clinical management of fluctuating movement disorders, e.g. Parkinson's disease (PD), is the large variability in manifestation of symptoms among patients. In this condition, frequent measurements which account for both patient-reported and objective assessments are needed in order to capture symptom fluctuations, with the purpose to optimize therapy. The main focus of this paper is to present a mobile-based system for enabling remote monitoring of PD patients from their home environment conditions. The system consists of a patient diary section for collecting patient-based self-assessments, a motor test section for collecting fine motor movements through upper limb motor tests, and a scheduler for restricting operation to a multitude of predetermined limited time intervals. The system processes and compiles time series data into different summary scores representing symptom severity. In addition, the paper presents a review of recent inventions which were filed after year 2000 in the field of telemedicine applications. The review includes a summary of systems and methods which enable remote symptom assessments of patients, not necessarily suffering from movement disorders, through repeated measurements and which take into account their subjective and/or objective health indicators. The findings conclude that there are a small number of inventions which collect subjective and objective health measures in telemedicine settings. Consequently, there is a lack of mechanisms that combine these two types of information into scores to provide a more in-depth assessment of the patient's general health, their motor and non-motor symptom fluctuations and treatment effects. The paper also provides a discussion concerning different approaches for analyzing and combining subjective and objective measures, and handling data from longitudinal studies.

Place, publisher, year, edition, pages
Bentham Science , 2013. Vol. 6, no 2, 127-135 p.
Keyword [en]
Remote patient monitoring, Parkinson’s disease, subjective, objective, telemedicine
National Category
Computer Systems
Research subject
Komplexa system - mikrodataanalys, PAULINA - Uppföljning av Parkinsonsymptom från hemmet
Identifiers
URN: urn:nbn:se:du-12729OAI: oai:DiVA.org:du-12729DiVA: diva2:637747
Available from: 2013-07-22 Created: 2013-07-22 Last updated: 2015-06-12Bibliographically approved
In thesis
1. Mobile systems for monitoring Parkinson's disease
Open this publication in new window or tab >>Mobile systems for monitoring Parkinson's disease
2014 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

A challenge for the clinical management of Parkinson's disease (PD) is the large within- and between-patient variability in symptom profiles as well as the emergence of motor complications which represent a significant source of disability in patients. This thesis deals with the development and evaluation of methods and systems for supporting the management of PD by using repeated measures, consisting of subjective assessments of symptoms and objective assessments of motor function through fine motor tests (spirography and tapping), collected by means of a telemetry touch screen device.

One aim of the thesis was to develop methods for objective quantification and analysis of the severity of motor impairments being represented in spiral drawings and tapping results. This was accomplished by first quantifying the digitized movement data with time series analysis and then using them in data-driven modelling for automating the process of assessment of symptom severity. The objective measures were then analysed with respect to subjective assessments of motor conditions. Another aim was to develop a method for providing comparable information content as clinical rating scales by combining subjective and objective measures into composite scores, using time series analysis and data-driven methods. The scores represent six symptom dimensions and an overall test score for reflecting the global health condition of the patient. In addition, the thesis presents the development of a web-based system for providing a visual representation of symptoms over time allowing clinicians to remotely monitor the symptom profiles of their patients. The quality of the methods was assessed by reporting different metrics of validity, reliability and sensitivity to treatment interventions and natural PD progression over time.

Results from two studies demonstrated that the methods developed for the fine motor tests had good metrics indicating that they are appropriate to quantitatively and objectively assess the severity of motor impairments of PD patients. The fine motor tests captured different symptoms; spiral drawing impairment and tapping accuracy related to dyskinesias (involuntary movements) whereas tapping speed related to bradykinesia (slowness of movements). A longitudinal data analysis indicated that the six symptom dimensions and the overall test score contained important elements of information of the clinical scales and can be used to measure effects of PD treatment interventions and disease progression. A usability evaluation of the web-based system showed that the information presented in the system was comparable to qualitative clinical observations and the system was recognized as a tool that will assist in the management of patients.

Place, publisher, year, edition, pages
Örebro: Örebro University, 2014. 87 p.
Series
Örebro Studies in Technology, ISSN 1650-8580 ; 57
Keyword
automatic assessments, data visualization, data-driven modelling, home assessments, information technology, mobile computing, objective measures, Parkinson’s disease, quantitative assessments, remote monitoring, spirography, symptom severity, tapping tests, telemedicine, telemetry, time series analysis, web technology.
National Category
Computer Systems
Research subject
Komplexa system - mikrodataanalys, PAULINA - Uppföljning av Parkinsonsymptom från hemmet
Identifiers
urn:nbn:se:du-13797 (URN)978-91-7668-988-2 (ISBN)
Public defence
2014-02-14, Clas Ohlsonsalen, Tenoren, Skomakargatan 1, Borlänge, 13:00 (English)
Opponent
Supervisors
Available from: 2014-02-13 Created: 2014-02-12 Last updated: 2015-06-12Bibliographically approved

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Citation style
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