ABSTRACT
BACKGROUND: There is a need for standardized and objective methods to measure postural instability (PI) and gait dysfunction in Parkinson's disease (PD) patients. Recent technological advances in wearable devices, including standard smartphones, may provide such measurements. OBJECTIVES: To test the feasibility of smartphones to detect PI during the Timed Up and Go (TUG) test. METHODS: Ambulatory PD patients, divided by item 30 (postural stability) of the motor Unified Parkinson's Disease Rating Scale (UPDRS) to those with a normal (score = 0, PD-NPT) and an abnormal (score ≥ 1, PD-APT) test and a group of healthy controls (HC) performed a 10-meter TUG while motion sensor data was recorded from a smartphone attached to their sternum using the EncephaLog application. RESULTS: In this observational study, 44 PD patients (21 PD-NPT and 23 PD-APT) and 22 HC similar in age and gender distribution were assessed. PD-APT differed significantly in all gait parameters when compared to PD-NPT and HC. Significant difference between PD-NPT and HC included only turning time (P < 0.006) and step-to-step correlation (P < 0.05). CONCLUSIONS: While high correlations were found between EncephaLog gait parameters and axial UPDRS items, the pull test was least correlated with EncephaLog measures. Motion sensor data from a smartphone can detect differences in gait and balance measures between PD with and without PI and HC.
Subject(s)
Parkinson Disease/diagnosis , Postural Balance , Smartphone , Aged , Case-Control Studies , Feasibility Studies , Female , Humans , Male , Middle Aged , Parkinson Disease/physiopathologyABSTRACT
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.
