Assessment of Walking Ability in Patients with Intermittent Claudication Using a Smartphone Accelerometer

Mark Greveling, Maaike de Bondt, Feike Weijzen,Robert H. Geelkerken,Mark Vlutters,Fabio S. Catarinella,Jan-Willem Hinnen

Journal of Scientific Innovation in Medicine(2021)

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Objectives: It is challenging to accurately monitor the progress of intermittent claudication patients during or after treatment. Furthermore, diagnostic tools for intermittent claudication are not always adequate to determine whether other diseases are the primary cause of any walking complaints. This makes it difficult to determine the optimal treatment for the patient and impairs proper follow-up. The objective was to investigate the feasibility of measuring disease specific changes in the gait pattern of intermittent claudication patients by using a smartphone accelerometer. Methods: This study is a clinical Proof-of-concept study. Included were 12 subjects. Seven of the subjects were healthy controls, the other five intermittent claudication patients. Raw accelerometer data was collected during a standardized walking test with an Iphone. Processed data was analyzed using the GaitPy package in Python, resulting in 20 different gait parameters per gait cycle. The data were divided, resulting in three groups: The control group, the patient group without symptoms and the patient group with active symptoms. Mann-Whitney U tests and Wilcoxon ranks test were used to examine the outcomes. Results: Five of the 20 parameters are significantly different between patients before symptoms and patients with active symptoms. All parameters except cadence and stride duration differ between our control group and the patients while experiencing symptoms. Nine of 20 parameters where significantly different between the control group and the patient group without symptoms. Conclusions: This study demonstrated the potential clinical applicability of measuring changes in intermittent claudication gait characteristics with a smartphone.
ehealth,gait analysis,gaitpy,intermittent claudication,smartphone
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