Remote at-home wearable-based gait assessments in Progressive Supranuclear Palsy compared to Parkinson's Disease.

BACKGROUND: Wearable sensors can differentiate Progressive Supranuclear Palsy (PSP) from Parkinson's Disease (PD) in laboratory settings but have not been tested in remote settings. OBJECTIVES: To compare gait and balance in PSP and PD remotely using wearable-based assessments. METHODS: Participants with probable PSP or probable/clinically established PD with reliable caregivers, still able to ambulate 10 feet unassisted, were recruited, enrolled, and consented remotely and instructed by video conference to operate a study-specific tablet solution (BioDigit Home ™) and to wear three inertial sensors (LEGSys™, BioSensics LLC, Newton, MA USA) while performing the Timed Up and Go, 5 × sit-to-stand, and 2-min walk tests. PSPRS and MDS-UPDRS scores were collected virtually or during routine clinical visits. RESULTS: Between November, 2021- November, 2022, 27 participants were screened of whom 3 were excluded because of technological difficulties. Eleven PSP and 12 PD participants enrolled, of whom 10 from each group had complete analyzable data. Demographics were well-matched (PSP mean age = 67.6 ± 1.3 years, 40% female; PD mean age = 70.3 ± 1.8 years, 40% female) while disease duration was significantly shorter in PSP (PSP 14 ± 3.5 months vs PD 87.9 ± 16.9 months). Gait parameters showed significant group differences with effect sizes ranging from d = 1.0 to 2.27. Gait speed was significantly slower in PSP: 0.45 ± 0.06 m/s vs. 0.79 ± 0.06 m/s in PD (d = 1.78, p < 0.001). CONCLUSION: Our study demonstrates the feasibility of measuring gait in PSP and PD remotely using wearable sensors. The study provides insight into digital biomarkers for both neurodegenerative diseases. TRIAL REGISTRATION: ClinicalTrials.gov Identifier: NCT04753320, first posted Febuary 15, 2021.

Smart-Home Concept for Remote Monitoring of Instrumental Activities of Daily Living (IADL) in Older Adults with Cognitive Impairment: A Proof of Concept and Feasibility Study.

Assessment of instrumental activities of daily living (IADL) is essential for the diagnosis and staging of dementia. However, current IADL assessments are subjective and cannot be administered remotely. We proposed a smart-home design, called IADLSys, for remote monitoring of IADL. IADLSys consists of three major components: (1) wireless physical tags (pTAG) attached to objects of interest, (2) a pendant-sensor to monitor physical activities and detect interaction with pTAGs, and (3) an interactive tablet as a gateway to transfer data to a secured cloud. Four studies, including an exploratory clinical study with five older adults with clinically confirmed cognitive impairment, who used IADLSys for 24 h/7 days, were performed to confirm IADLSys feasibility, acceptability, adherence, and validity of detecting IADLs of interest and physical activity. Exploratory tests in two cases with severe and mild cognitive impairment, respectively, revealed that a case with severe cognitive impairment either overestimated or underestimated the frequency of performed IADLs, whereas self-reporting and objective IADL were comparable for the case with mild cognitive impairment. This feasibility and acceptability study may pave the way to implement the smart-home concept to remotely monitor IADL, which in turn may assist in providing personalized support to people with cognitive impairment, while tracking the decline in both physical and cognitive function.

Utilizing speech analysis to differentiate progressive supranuclear palsy from Parkinson's disease.

INTRODUCTION: Distinguishing Parkinson's disease (PD) from Progressive supranuclear palsy (PSP) at early disease stages is important for clinical trial enrollment and clinical care/prognostication. METHODS: We recruited 21 participants with PSP(n = 11) or PD(n = 10) with reliable caregivers. Standardized passage reading, counting, and sustained phonation were recorded on the BioDigit Home tablet (BioSensics LLC, Newton, MA USA), and speech features from the assessments were analyzed using the BioDigit Speech platform (BioSensics LLC, Newton, MA USA). An independent t-test was performed to compare each speech feature between PSP and PD participants. We also performed Spearman's correlations to evaluate associations between speech measures and clinical scores (e.g., PSP rating scales and MoCA). In addition, the model's performance in classifying PSP and PD was evaluated using Rainbow passage reading analysis. RESULTS: During Rainbow passage reading, PSP participants had a significantly slower articulation rate (2.45(0.49) vs 3.60(0.47) words/minute), lower speech-to-pause ratio (2.33(1.08) vs 3.67(1.18)), intelligibility dynamic time warping (DTW, 0.26(0.19) vs 0.53(0.26)), and similarity DTW (0.43(0.27) vs 0.67(0.13)) compared to PD participants. PSP participants also had longer pause times (17.24(5.47) vs 8.45(3.13) sec) and longer total signal times (52.44(6.67) vs (36.67(6.73) sec) when reading the passage. In terms of the phonation 'a', PSP participants showed a significant higher spectral entropy, spectral centroid, and spectral spread compared to PD participants and no differences were found for phonation 'e'. PD participants had more accurate reverse number counts than PSP participants (14.89(3.86) vs 7.36(4.67)). PSP Rating Scale (PSPRS) dysarthria (r = 0.79, p = 0.004) and bulbar item scores (r = 0.803, p = 0.005) were positively correlated with articulation rate in reverse number counts. Correct reverse number counts were positively correlated with total Montreal Cognitive Assessment scores (r = 0.703, p = 0.016). Machine learning models using passage reading-derived measures obtained an AUC of 0.93, and the sensitivity/specificity in correctly classifying PSP and PD participants were 0.95 and 0.90, respectively. CONCLUSION: Our study demonstrates the feasibility of differentiating PSP from PD using a digital health technology platform. Further multi-center studies are needed to expand and validate our initial findings.