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Author Tamir-Ostrover, H.; Hassin-Baer, S.; Fay-Karmon, T.; Friedman, J. url  doi
openurl 
  Title Quantifying Changes in Dexterity as a Result of Piano Training in People with Parkinson's Disease Type Journal Article
  Year 2024 Publication Sensors (Basel, Switzerland) Abbreviated Journal Sensors (Basel)  
  Volume (down) 24 Issue 11 Pages  
  Keywords Humans; *Parkinson Disease/physiopathology; Pilot Projects; Male; Aged; Female; Quality of Life; Middle Aged; Motor Skills/physiology; Music; Surveys and Questionnaires; Activities of Daily Living; Fingers/physiology/physiopathology; Parkinson's disease; dexterity; force sensors; music; piano; sonification; training; uncontrolled manifold  
  Abstract People with Parkinson's disease often show deficits in dexterity, which, in turn, can lead to limitations in performing activities of daily life. Previous studies have suggested that training in playing the piano may improve or prevent a decline in dexterity in this population. In this pilot study, we tested three participants on a six-week, custom, piano-based training protocol, and quantified dexterity before and after the intervention using a sensor-enabled version of the nine-hole peg test, the box and block test, a test of finger synergies using unidimensional force sensors, and the Quantitative Digitography test using a digital piano, as well as selected relevant items from the motor parts of the MDS-Unified Parkinson's Disease Rating Scale (MDS-UPDRS) and the Parkinson's Disease Questionnaire (PDQ-39) quality of life questionnaire. The participants showed improved dexterity following the training program in several of the measures used. This pilot study proposes measures that can track changes in dexterity as a result of practice in people with Parkinson's disease and describes a potential protocol that needs to be tested in a larger cohort.  
  Address Sagol School of Neuroscience, Tel Aviv University, Tel Aviv 6997801, Israel  
  Corporate Author Thesis  
  Publisher Place of Publication Editor  
  Language English Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 1424-8220 ISBN Medium  
  Area Expedition Conference  
  Notes PMID:38894110; PMCID:PMC11174779 Approved no  
  Call Number Serial 124  
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Author Krasovsky, T.; Weiss, P.L.; Zuckerman, O.; Bar, A.; Keren-Capelovitch, T.; Friedman, J. pdf  url
doi  openurl
  Title DataSpoon: Validation of an Instrumented Spoon for Assessment of Self-Feeding Type Journal Article
  Year 2020 Publication Sensors (Basel, Switzerland) Abbreviated Journal Sensors (Basel)  
  Volume (down) 20 Issue 7 Pages  
  Keywords concurrent validity; feasibility; kinematics; outcome assessment; rehabilitation  
  Abstract Clinically feasible assessment of self-feeding is important for adults and children with motor impairments such as stroke or cerebral palsy. However, no validated assessment tool for self-feeding kinematics exists. This work presents an initial validation of an instrumented spoon (DataSpoon) developed as an evaluation tool for self-feeding kinematics. Ten young, healthy adults (three male; age 27.2 +/- 6.6 years) used DataSpoon at three movement speeds (slow, comfortable, fast) and with three different grips: “natural”, power and rotated power grip. Movement kinematics were recorded concurrently using DataSpoon and a magnetic motion capture system (trakSTAR). Eating events were automatically identified for both systems and kinematic measures were extracted from yaw, pitch and roll (YPR) data as well as from acceleration and tangential velocity profiles. Two-way, mixed model Intraclass correlation coefficients (ICC) and 95% limits of agreement (LOA) were computed to determine agreement between the systems for each kinematic variable. Most variables demonstrated fair to excellent agreement. Agreement for measures of duration, pitch and roll exceeded 0.8 (excellent agreement) for >80% of speed and grip conditions, whereas lower agreement (ICC < 0.46) was measured for tangential velocity and acceleration. A bias of 0.01-0.07 s (95% LOA [-0.54, 0.53] to [-0.63, 0.48]) was calculated for measures of duration. DataSpoon enables automatic detection of self-feeding using simple, affordable movement sensors. Using movement kinematics, variables associated with self-feeding can be identified and aid clinical reasoning for adults and children with motor impairments.  
  Address Department of Physical Therapy, Sackler Faculty of Medicine, Tel Aviv University, Tel Aviv 6997801, Israel  
  Corporate Author Thesis  
  Publisher Place of Publication Editor  
  Language English Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 1424-8220 ISBN Medium  
  Area Expedition Conference  
  Notes PMID:32283624; PMCID:PMC7180859 Approved no  
  Call Number Serial 104  
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