ABSTRACT
Static balance tests are conducted in various clinics for diagnosis and treatment adjustment. As a result of population aging, the accessibility of these tests should be increased, in the clinic, and for remote patient examination. A number of publications have already conducted static balance evaluations using the sensors embedded in a smartphone. This study focuses on the applicability of using smartphone-based balance assessment on a large scale while considering ease of use, safety, and reliability. The Mon4t® app was used to acquire the postural motion using different smartphone devices, different smartphone locations, and various standing postures. The signals derived from the app were compared to the center of pressure displacement derived from a force plate. The results showed moderate to high agreement between the two methods, particularly at the tandem stance (0.69 ≤ r ≤ 0.91). Preliminary data collection was conducted on three healthy participants, followed by 50 additional healthy volunteers, aged 65+. The results demonstrated that the Mon4t app can serve as an accessible and inexpensive static balance assessment tool, both in clinical settings and for remote patient monitoring, which is key for enabling telehealth.
Subject(s)
Postural Balance , Smartphone , Healthy Volunteers , Humans , Posture , Reproducibility of ResultsABSTRACT
OBJECTIVES: We aimed to characterize parkinsonian features and gait performance of psychiatric patients on neuroleptics (PPN) and to compare them to Parkinson's disease (PD) and healthy controls (HC). METHODS: Hospitalized PPN (n = 27) were recruited, examined, and rated for parkinsonian signs according to the motor part of the Movement Disorders Society Unified Parkinson's Disease Rating Scale and performed a 10-m "timed-up-and-go" (TUG) test with a smartphone-based motion capture system attached to their sternum. Gait parameters and mUPDRS scores were compared to those of consecutive age-matched PD patients (n = 18) and HC (n = 27). RESULTS: Psychiatric patients on neuroleptics exhibited parkinsonism (mUPDRS score range: 8-44) but less than that of PD patients (18.2 ± 9.2 vs 29.8 ± 10.3, P = 0.001). TUG times were slower for PPN and PD versus HC (total: 30.6 ± 7.6 seconds vs 30.0 ± 7.3 seconds vs 20.0 ± 3.2 seconds, straight walking: 10.6 ± 2.7 seconds vs 10.6 ± 2.4 seconds vs 6.8 ± 1.2 seconds) (P < 0.001), and cadence and step length were similar among PPN and PD and different from HC as well. Although their gait speed was slower than HC but similar to PD, PPN had lower mediolateral sway (4.3 ± 1.1 cm vs 6.7 ± 2.9 cm vs 6.9 ± 2.9 cm, respectively, P < 0.001) than both. CONCLUSIONS: Parkinsonism is very common in hospitalized PPN, but usually milder than that of PD. It seems that wearable sensor-based technology for assessing gait and balance may present a more sensitive and quantitative tool to detect clinical aspects of neuroleptic-induced parkinsonism than standard clinical ratings.