Inertial Sensor Algorithms to Characterize Turning in Neurological Patients with Turn Hesitations

Vrutangkumar V. Shah, Carolin Curtze, Martina Mancini, Patricia Carlson-Kuhta, John Nutt, Christopher M. Gomez, Mahmoud El-Gohary, Fay Horak, James Mcnames

Research output: Contribution to journalArticlepeer-review

Abstract

Background. One difficulty in turning algorithm design for inertial sensors is detecting two discrete turns in the same direction, close in time. A second difficulty is under-estimation of turn angle due to short-duration hesitations by people with neurological disorders. We aim to validate and determine the generalizability of a: I. Discrete Turn Algorithm for variable and sequential turns close in time and II: Merged Turn Algorithm for a single turn angle in the presence of hesitations. Methods: We validated the Discrete Turn Algorithm with motion capture in healthy controls (HC, n=10) performing a spectrum of turn angles. Subsequently, the generalizability of the Discrete Turn Algorithm and associated, Merged Turn Algorithm were tested in people with Parkinsons disease (PD, n =124), spinocerebellar ataxia (SCA, n=51), and HC (n=125). Results: The Discrete Turn Algorithm shows improved agreement with optical motion capture and with known turn angles, compared to our previous algorithm by El-Gohary et al. The Merged Turn algorithm that merges consecutive turns in the same direction with short hesitations resulted in turn angle estimates closer to a fixed 180-degree turn angle in the PD, SCA, and HC subjects compared to our previous turn algorithm. Additional metrics were proposed to capture turn hesitations in PD and SCA. Conclusion: The Discrete Turn Algorithm may be particularly useful to characterize turns when the turn angle is unknown, i.e. during free-living conditions. The Merged Turn algorithm is recommended for clinical tasks in which the single-turn angle is known, especially for patients who hesitate while turning.

Original languageEnglish (US)
JournalIEEE Transactions on Biomedical Engineering
DOIs
StateAccepted/In press - 2020

Keywords

  • Estimation
  • Foot
  • Optical filters
  • Optical sensors
  • Parkinson's disease (PD)
  • Sensors
  • Signal processing algorithms
  • Spinocerebellar ataxia (SCA)
  • Turning
  • Turning
  • healthy controls (HC)
  • inertial sensors
  • mobility

ASJC Scopus subject areas

  • Biomedical Engineering

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