Objective: Huntington’s disease (HD) patients cope with unique gait disturbances. Proper evaluation of gait in these patients is highly needed. Dyskinesia may negatively affect validity of gait assessments. Quantitative gait evaluation can currently be performed only in dedicated gait labs. This is a feasibility study aimed to assess an HD gait-analysis App using a standard smartphone, accessible for every physician and patient.

Background: Huntington’s disease (HD) patients cope with unique gait disturbances.

Method: Participants’ gait was evaluated using EncephaLog App, using a smartphone’s integral accelerometers and gyroscope for capturing the subject’s trajectory. For each subject, three Timed up-and-go test (TUG) sessions were recorded. Raw data was sent to a server where several gait biomarkers were extracted. Patients were also evaluated clinically ̶ physical, cognitive and functional data was collected.

Results: 25 genetically confirmed HD patients (13 females) participated: Mean age: 52.3±13.79; CAG length:44.5±5.182; Disease duration: 6.7 years±4.12;UHDRS total score:38.25±14.48; UHDRS dyskinesia score:1.02 ±1.14;UHDRS gait score:1.04±0.55; Total functional capacity: 5.68±3.132; Mean MoCA score:18.6±4.55. There were substantial correlations between different gait parameters measured by EncephaLog system, for example: Stand-up time and Sit-down time (r=0.58, p=0.003), Rotation time and step length (r=0.61, p=0.0016), Medio-lateral sway and steps frequency (r=0.55, p=0.0048). Such correlations were kept for patients with high UHDRS dyskinesia scores. Correlation were found between EncephaLog outputs and Gait UHDRS scores (rotation time: r=0.72, p=0.0001; sit-down time: r=0.52, p=0.011; Medio-lateral sway: r=0.45, p=0.032).

Conclusion: EncephaLog system was able to assess gait parameters in HD with acceptable accuracy. Participants cooperated well with the smartphone assessment, despite cognitive problems. Although chorea ̶ a common symptom in HD ̶ challenges biomarker-extraction from raw data, we found that using a combination of several motion-capturing sensors was helpful for identifying key events in the TUG sequence. Further studies will be performed to validate the precision of quantitative gait analysis by EncephaLog App.

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MDS Abstracts - https://www.mdsabstracts.org/abstract/assessment-of-gait-in-huntingtons-disease-patients-using-encephalog-smartphones-application/