Dealing with the heterogeneous presentations of freezing of gait: how reliable are the freezing index and heart rate for freezing detection?

Journal of NeuroEngineering and Rehabilitation

Research

Ian Cameron¹  Helena Cockx²  Richard van Wezel³  Ying Wang⁴  Bastiaan R. Bloem⁵  Jorik Nonnekes⁶ 

[1] Biomedical Signals and Systems Group, Faculty of Electrical Engineering, Mathematics and Computer Science (EEMCS), University of Twente, Enschede, The Netherlands;OnePlanet Research Center, Nijmegen, The Netherlands;Department of Biophysics, Donders Institute for Brain, Cognition and Behaviour, Radboud University, P.O. Box 9102, Heyendaalseweg 135, 6525AJ, Nijmegen, The Netherlands;Department of Biophysics, Donders Institute for Brain, Cognition and Behaviour, Radboud University, P.O. Box 9102, Heyendaalseweg 135, 6525AJ, Nijmegen, The Netherlands;Biomedical Signals and Systems Group, Faculty of Electrical Engineering, Mathematics and Computer Science (EEMCS), University of Twente, Enschede, The Netherlands;Department of Biophysics, Donders Institute for Brain, Cognition and Behaviour, Radboud University, P.O. Box 9102, Heyendaalseweg 135, 6525AJ, Nijmegen, The Netherlands;Biomedical Signals and Systems Group, Faculty of Electrical Engineering, Mathematics and Computer Science (EEMCS), University of Twente, Enschede, The Netherlands;ZGT Academy, Ziekenhuisgroep Twente, Almelo, The Netherlands;Department of Neurology, Center of Expertise for Parkinson and Movement Disorders, Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Center, Nijmegen, The Netherlands;Department of Rehabilitation, Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Center, Nijmegen, The Netherlands;Department of Rehabilitation, Sint Maartenskliniek, Nijmegen, The Netherlands;

关键词: Freezing of gait;    Movement disorders;    Wearable sensors;    Heart rate;    Accelerometer;    Freezing index;   

DOI  :  10.1186/s12984-023-01175-y

 received in 2021-07-20, accepted in 2023-04-12,  发布年份 2023

来源: Springer

【 摘 要 】

BackgroundFreezing of gait (FOG) is an unpredictable gait arrest that hampers the lives of 40% of people with Parkinson’s disease. Because the symptom is heterogeneous in phenotypical presentation (it can present as trembling/shuffling, or akinesia) and manifests during various circumstances (it can be triggered by e.g. turning, passing doors, and dual-tasking), it is particularly difficult to detect with motion sensors. The freezing index (FI) is one of the most frequently used accelerometer-based methods for FOG detection. However, it might not adequately distinguish FOG from voluntary stops, certainly for the akinetic type of FOG. Interestingly, a previous study showed that heart rate signals could distinguish FOG from stopping and turning movements. This study aimed to investigate for which phenotypes and evoking circumstances the FI and heart rate might provide reliable signals for FOG detection.MethodsSixteen people with Parkinson’s disease and daily freezing completed a gait trajectory designed to provoke FOG including turns, narrow passages, starting, and stopping, with and without a cognitive or motor dual-task. We compared the FI and heart rate of 378 FOG events to baseline levels, and to stopping and normal gait events (i.e. turns and narrow passages without FOG) using mixed-effects models. We specifically evaluated the influence of different types of FOG (trembling vs akinesia) and triggering situations (turning vs narrow passages; no dual-task vs cognitive dual-task vs motor dual-task) on both outcome measures.ResultsThe FI increased significantly during trembling and akinetic FOG, but increased similarly during stopping and was therefore not significantly different from FOG. In contrast, heart rate change during FOG was for all types and during all triggering situations statistically different from stopping, but not from normal gait events.ConclusionWhen the power in the locomotion band (0.5–3 Hz) decreases, the FI increases and is unable to specify whether a stop is voluntary or involuntary (i.e. trembling or akinetic FOG). In contrast, the heart rate can reveal whether there is the intention to move, thus distinguishing FOG from stopping. We suggest that the combination of a motion sensor and a heart rate monitor may be promising for future FOG detection.

【 授权许可】

CC BY   
© The Author(s) 2023. corrected publication 2023

【 图 表 】

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