Optimal sensor placement for measuring physical activity with a 3D accelerometer

Accelerometer-based activity monitors are popular for monitoring physical activity. In this study, we investigated optimal sensor placement for increasing the quality of studies that utilize accelerometer data to assess physical activity. We performed a two-staged study, focused on sensor location and type of mounting. Ten subjects walked at various walking speeds on a treadmill, performed a deskwork protocol, and walked on level ground, while simultaneously wearing five ProMove2 sensors with a snug fit on an elastic waist belt. We found that sensor location, type of activity, and their interaction-effect affected sensor output. The most lateral positions on the waist belt were the least sensitive for interference. The effect of mounting was explored, by making two subjects repeat the experimental protocol with sensors more loosely fitted to the elastic belt. The loose fit resulted in lower sensor output, except for the deskwork protocol, where output was higher. In order to increase the reliability and to reduce the variability of sensor output, researchers should place activity sensors on the most lateral position of a participant's waist belt. If the sensor hampers free movement, it may be positioned slightly more forward on the belt. Finally, sensors should be fitted tightly to the body

Negative symptoms predict high relapse rates and both predict less favorable functional outcome in first episode psychosis, independent of treatment strategy

BACKGROUND: In first episode psychosis (FEP) baseline negative symptoms (BNS) and relapse both predict less favorable functional outcome. Relapse-prevention is one of the most important goals of treatment. Apart from discontinuation of antipsychotics, natural causes of relapse are unexplained. We hypothesized that BNS, apart from predicting worse functional outcome, might also increase relapse risk. METHODS: We performed a post-hoc analysis of 7-year follow-up data of a FEP cohort (n = 103) involved in a dose-reduction/discontinuation (DR) vs. maintenance treatment (MT) trial. We examined: 1) what predicted relapse, 2) what predicted functional outcome, and 3) if BNS predicted relapse, whether MT reduced relapse rates compared to DR. After remission patients were randomly assigned to DR or MT for 18 months. Thereafter, treatment was uncontrolled. OUTCOMES: BNS and duration of untreated psychosis (DUP) predicted relapse. Number of relapses, BNS, and treatment strategy predicted functional outcome. BNS was the strongest predictor of relapse, while number of relapses was the strongest predictor of functional outcome above BNS and treatment strategy. Overall and within MT, but not within DR, more severe BNS predicted significantly higher relapse rates. Treatment strategies did not make a difference in relapse rates, regardless of BNS severity. INTERPRETATION: BNS not only predicted worse functional outcome, but also relapses during follow-up. Since current low dose maintenance treatment strategies did not prevent relapse proneness in patients with more severe BNS, resources should be deployed to find optimal treatment strategies for this particular group of patients

Reprint of:Negative symptoms predict high relapse rates and both predict less favorable functional outcome in first episode psychosis, independent of treatment strategy

Background: In first episode psychosis (FEP) baseline negative symptoms (BNS) and relapse both predict less favorable functional outcome. Relapse-prevention is one of the most important goals of treatment. Apart from discontinuation of antipsychotics, natural causes of relapse are unexplained. We hypothesized that BNS, apart from predicting worse functional outcome, might also increase relapse risk. Methods: We performed a post-hoc analysis of 7-year follow-up data of a FEP cohort (n = 103) involved in a dose-reduction/discontinuation (DR) vs. maintenance treatment (MT) trial. We examined: 1) what predicted relapse, 2) what predicted functional outcome, and 3) if BNS predicted relapse, whether MT reduced relapse rates compared to DR. After remission patients were randomly assigned to DR or MT for 18 months. Thereafter, treatment was uncontrolled. Outcomes: BNS and duration of untreated psychosis (DUP) predicted relapse. Number of relapses, BNS, and treatment strategy predicted functional outcome. BNS was the strongest predictor of relapse, while number of relapses was the strongest predictor of functional outcome above BNS and treatment strategy. Overall and within MT, but not within DR, more severe BNS predicted significantly higher relapse rates. Treatment strategies did not make a difference in relapse rates, regardless of BNS severity. Interpretation: BNS not only predicted worse functional outcome, but also relapses during follow-up. Since current low dose maintenance treatment strategies did not prevent relapse proneness in patients with more severe BNS, resources should be deployed to find optimal treatment strategies for this particular group of patients. (C) 2019 Elsevier B.V. All rights reserved

Observation of two relaxation mechanisms in transport between spin split edge states at high imbalance

Using a quasi-Corbino geometry to directly study electron transport between spin-split edge states, we find a pronounced hysteresis in the I-V curves, originating from slow relaxation processes. We attribute this long-time relaxation to the formation of a dynamic nuclear polarization near the sample edge. The determined characteristic relaxation times are 25 s and 200 s which points to the presence of two different relaxation mechanisms. The two time constants are ascribed to the formation of a local nuclear polarization due to flip-flop processes and the diffusion of nuclear spins.Comment: Submitted to PR