Tele-Rehabilitation of Upper Limb Function in Stroke Patients using Microsoft Kinect

Bidragets oversatte titel: Tele-rehabilitering af Overekstremitetsfunktion i apopleksipatienter ved brug af Microsoft Kinect

Daniel Simonsen

Publikation: Ph.d.-afhandling

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Abstract

Stroke is a major cause of death and disability worldwide. The damage or death of brain cells caused by a stroke affects brain function and leads to deficits in sensory and/or motor function. As a consequence, a stroke can have a significantly negative impact on the patient’s ability to perform activities of daily living and therefore also affect the patient’s quality of life. Stroke patients may regain function through intensive physical rehabilitation, but often they do not recover their original functional level. The incomplete recovery in some patients might be related to e.g. stroke severity, lack of motivation for training, or insufficient and/or non-optimal training in the initial weeks following the stroke.
A threefold increase in the number of people living past the age of 80 in 2050, combined with the increasing number of surviving stroke patients, will very likely lead to a significant increase in the number of stroke patients in need of rehabilitation. This will put further pressure on healthcare systems that are already short on resources. As a result of this, the amount of therapeutic supervision and support per stroke patient will most likely decrease, thereby affecting negatively the quality of rehabilitation.
Technology-based rehabilitation systems could very likely offer a way of maintaining the current quality of rehabilitation services by supporting therapists. Repetition of routine exercises may be performed automatically by these systems with only limited or even no need for human supervision. The requirements to such systems are highly dependent on the training environment and the physical and mental abilities of the stroke patient. Therefore, the ideal rehabilitation system should be highly versatile, but also low-cost. These systems may even be used to support patients at remote sites, e.g. in the patient’s own home, thus serving as tele-rehabilitation systems.
In this Ph.D. project the low-cost and commercially available Microsoft Kinect sensor was used as a key component in three studies performed to investigate the feasibility of supporting and assessing upper limb function and training in stroke patients by use of a Microsoft Kinect sensor based tele-rehabilitation system. The outcome of the three studies showed that the Microsoft Kinect sensor can successfully be used for closed-loop control of functional electrical stimulation for supporting hand function training in stroke patients (Study I), delivering visual feedback to stroke patients during upper limb training (Study II), and automatization of a validated motor function test (Study III).
The systems described in the three studies could be developed further in many possible ways, e.g. new studies could investigate adaptive regulation of the intensity used by the closed-loop FES system described in Study I, different types of feedback to target a larger group of stroke patients (Study II), and implementation of more sensors to allow a more detailed kinematic analysis of the stroke patients (Study III). New studies could also test a combined version of the systems described in this thesis and test the system in the patients’ own homes as part of a clinical trial investigating the effect of long-term training on motor function and/or non-physical parameters, e.g. motivational level and quality of life.
Bidragets oversatte titelTele-rehabilitering af Overekstremitetsfunktion i apopleksipatienter ved brug af Microsoft Kinect
OriginalsprogEngelsk
Udgiver
ISBN'er, elektronisk978-87-7112-923-6
DOI
StatusUdgivet - 2017

Bibliografisk note

PhD supervisor:
Professor, Dr. scient., Ph.D. Ole Kæseler Andersen, Aalborg University

Assistant PhD supervisor:
Associate Professor, Ph.D., Erika G. Spaich, Aalborg University

Emneord

  • Stroke
  • Functional electrical stimulation
  • Microsoft Kinect
  • Feedback
  • Automatization
  • Motor function

Citationsformater