A Moment of Mindfulness: Computer-Mediated Mindfulness Practice Increases State Mindfulness

Three studies investigated the use of a 5-minute, computer-mediated mindfulness practice in increasing levels of state mindfulness. In Study 1, 54 high school students completed the computer-mediated mindfulness practice in a lab setting and Toronto Mindfulness Scale (TMS) scores were measured before and after the practice. In Study 2 (N = 90) and Study 3 (N = 61), the mindfulness practice was tested with an entirely online sample to test the delivery of the 5-minute mindfulness practice via the internet. In Study 2 and 3, we found a significant increase in TMS scores in the mindful condition, but not in the control condition. These findings highlight the impact of a brief, mindfulness practice for single-session, computer-mediated use to increase mindfulness as a state

PROLIFIC: A Fast and Robust Profile-Likelihood-Based Muscle Onset Detection in Electromyogram Using Discrete Fibonacci Search

A stochastic scheme, namely, PLM-Lap, has recently been propounded, which relies on the profile likelihood (PL) constructed with a Laplace distribution for estimating muscle activation onsets (MAOs) in surface electromyographic (sEMG) data. The MAO detection accuracy and robustness of the PLM-Lap have been empirically shown to be better than those of several state-of-the-art approaches. The algorithm designates the data point index associated with the maximum of the PL function as an onset occurrence by regarding every sEMG data point as a candidate onset and hence exhaustively evaluating the objective function. This article concerns an expedient and faster approach premised on the discrete Fibonacci search (DFS) to locate the maximum of the discrete PL function. The experimental results support that both the exhaustive and DFS procedures are equivalent in a statistical sense, whereas the latter offers impressive computational savings by a factor of approximately 90. Owing to the speed-up, the accuracy of MAO estimation may further be enhanced by modeling the sEMG data with a set of PL functions, each one built using a suitable probability distribution, and picking the estimate from the best model. Three statistical criteria, i.e., Kolmogorov-Smirnov, Lilliefors, and Anderson-Darling test, for choosing the probability distribution are recommended. A freely downloadable MATLAB package, namely PROLIFIC, meant for sEMG onset detection is available on MATLAB File Exchange from the following link: https://www.mathworks.com/matlabcentral/fileexchange/76495-prolific-profile-likelihood-based-on-fibonacci-search

Feasibility of an online mindfulness program for stress management – a randomized, controlled trail

Abstract Background Chronic stress affects many Americans. Stress management programs may be prohibitively expensive or have limited access. Purpose This study aims to determine feasibility of an 8-week Internet-based stress management program (ISM) based on mindfulness principles in reducing stress in a 12-week, parallel, randomized, controlled trial. Methods Participants were randomly allocated to ISM, ISM plus online message board (ISM+), or control groups. Perceived stress, mindfulness, self-transcendence, psychological well-being, vitality, and quality of life were measured at baseline, week 8, and week 12 using standard validated questionnaires. Results ISM and ISM+ groups demonstrated statistically significant improvements compared with control on all measures except vitality and physical health. Conclusions The ISM program effectively and sustainably reduced measures of stress. The magnitude of improvement is comparable to traditional mindfulness programs, although fewer participants were engaged. This feasibility study provides strong support for online stress management programs, which increase access at a fraction of cost of traditional programs