Different effects of essential tremor and Parkinsonian tremor on multiscale dynamics of hand tremor.

OBJECTIVE: Essential tremor (ET) and Parkinsonian tremor (PT) are often clinically misdiagnosed due to the overlapping characteristics of their hand tremor. We aim to examine if ET and PT influence the multiscale dynamics of hand tremor, as quantified using complexity, differently, and if such complexity metric is of promise to help identify ET from PT. METHODS: Forty-eight participants with PT and 48 with ET performed two 30-second tests within each of the following conditions: sitting while resting arms or outstretching arms horizontally. The hand tremor was captured by accelerometers secured to the dorsum of each hand. The complexity was quantified using multiscale entropy. RESULTS: Compared to PT group, ET group had lower complexity of both hands across conditions (F > 34.2, p < 0.001). Lower complexity was associated with longer disease duration (r2 > 0.15, p < 0.009) in both PT and ET, and within PT, greater Unified Parkinson's Disease Rating Scale-III UPDRS-III scores (r2 > 0.18, p < 0.009). Receiver-operating-characteristic curves revealed that the complexity metric can distinguish ET from PT (area-under-the-curve > 0.77, cut-off value = 48 (postural), 49 (resting)), which was confirmed in a separate dataset with ET and PT that were clearly diagnosed in prior work. CONCLUSIONS: The PT and ET have different effects on hand tremor complexity, and this metric is promising to help the identification of ET and PT, which still needs to be confirmed in future studies. SIGNIFICANCE: The characteristics of multiscale dynamics of the hand tremor, as quantified by complexity, provides novel insights into the different pathophysiology between ET and PT.

Simple Smartphone-Based Assessment of Gait Characteristics in Parkinson Disease: Validation Study.

BACKGROUND: Parkinson disease (PD) is a common movement disorder. Patients with PD have multiple gait impairments that result in an increased risk of falls and diminished quality of life. Therefore, gait measurement is important for the management of PD. OBJECTIVE: We previously developed a smartphone-based dual-task gait assessment that was validated in healthy adults. The aim of this study was to test the validity of this gait assessment in people with PD, and to examine the association between app-derived gait metrics and the clinical and functional characteristics of PD. METHODS: Fifty-two participants with clinically diagnosed PD completed assessments of walking, Movement Disorder Society Unified Parkinson Disease Rating Scale III (UPDRS III), Montreal Cognitive Assessment (MoCA), Hamilton Anxiety (HAM-A), and Hamilton Depression (HAM-D) rating scale tests. Participants followed multimedia instructions provided by the app to complete two 20-meter trials each of walking normally (single task) and walking while performing a serial subtraction dual task (dual task). Gait data were simultaneously collected with the app and gold-standard wearable motion sensors. Stride times and stride time variability were derived from the acceleration and angular velocity signal acquired from the internal motion sensor of the phone and from the wearable sensor system. RESULTS: High correlations were observed between the stride time and stride time variability derived from the app and from the gold-standard system (r=0.98-0.99, P<.001), revealing excellent validity of the app-based gait assessment in PD. Compared with those from the single-task condition, the stride time (F1,103=14.1, P<.001) and stride time variability (F1,103=6.8, P=.008) in the dual-task condition were significantly greater. Participants who walked with greater stride time variability exhibited a greater UPDRS III total score (single task: ß=.39, P<.001; dual task: ß=.37, P=.01), HAM-A (single-task: ß=.49, P=.007; dual-task: ß=.48, P=.009), and HAM-D (single task: ß=.44, P=.01; dual task: ß=.49, P=.009). Moreover, those with greater dual-task stride time variability (ß=.48, P=.001) or dual-task cost of stride time variability (ß=.44, P=.004) exhibited lower MoCA scores. CONCLUSIONS: A smartphone-based gait assessment can be used to provide meaningful metrics of single- and dual-task gait that are associated with disease severity and functional outcomes in individuals with PD.

Analysis and Comparison of GPS Precipitable Water Estimates between Two Nearby Stations on Tahiti Island.

Since Bevis first proposed Global Positioning System (GPS) meteorology in 1992, the precipitable water (PW) estimates retrieved from Global Navigation Satellite System (GNSS) networks with high accuracy have been widely used in many meteorological applications. The proper estimation of GNSS PW can be affected by the GNSS processing strategy as well as the local geographical properties of GNSS sites. To better understand the impact of these factors, we compare PW estimates from two nearby permanent GPS stations (THTI and FAA1) in the tropical Tahiti Island, a basalt shield volcano located in the South Pacific, with a mean slope of 8% and a diameter of 30 km. The altitude difference between the two stations is 86.14 m, and their horizontal distance difference is 2.56 km. In this paper, Bernese GNSS Software Version 5.2 with precise point positioning (PPP) and Vienna mapping function 1 (VMF1) was applied to estimate the zenith tropospheric delay (ZTD), which was compared with the International GNSS Service (IGS) Final products. The meteorological parameters sourced from the European Center for Medium-Range Weather Forecasts (ECMWF) and the local weighted mean temperature ( T m ) model were used to estimate the GPS PW for three years (May 2016 to April 2019). The results show that the differences of PW between two nearby GPS stations is nearly a constant with value 1.73 mm. In our case, this difference is mainly driven by insolation differences, the difference in altitude and the wind being only second factors.