Managing Diabetes Using Mobiab: Long-Term Case Study of the Impact of a Mobile App on Self-management.

Background: This paper describes the development of a mobile app for diabetes mellitus (DM) control and self-management and presents the results of long-term usage of this system in the Czech Republic. DM is a chronic disease affecting large numbers of people worldwide, and this number is continuously increasing. There is massive potential to increase adherence to self-management of DM with the use of smartphones and digital therapeutics interventions.

Human chronotype: Comparison of questionnaires and wrist-worn actigraphy.

In this work, we investigated the accuracy of chronotype estimation from actigraphy while evaluating the required recording length and stability over time. Chronotypes have an important role in chronobiological and sleep research. In outpatient studies, chronotypes are typically evaluated by questionnaires.

Classification of Actigraphy Records from Bipolar Disorder Patients Using Slope Entropy: A Feasibility Study.

Bipolar Disorder (BD) is an illness with high prevalence and a huge social and economic impact. It is recurrent, with a long-term evolution in most cases. Early treatment and continuous monitoring have proven to be very effective in mitigating the causes and consequences of BD.

Motor activity patterns can distinguish between interepisode bipolar disorder patients and healthy controls.

Background: Bipolar disorder (BD) is linked to circadian rhythm disruptions resulting in aberrant motor activity patterns. We aimed to explore whether motor activity alone, as assessed by longitudinal actigraphy, can be used to classify accurately BD patients and healthy controls (HCs) into their respective groups.

Methods: Ninety-day actigraphy records from 25 interepisode BD patients (ie, Montgomery-Asberg Depression Rating Scale (MADRS) and Young Mania Rating Scale (YMRS) < 15) and 25 sex- and age-matched HCs were used in order to identify latent actigraphic biomarkers capable of discriminating between BD patients and HCs.

Weight loss in conservative treatment of obesity in women is associated with physical activity and circadian phenotype: a longitudinal observational study.

Introduction: The study investigates the association between circadian phenotype (CP), its stability (interdaily stability - IS) and physical activity (PA) in a weight loss (WL) programme.

Methods: Seventy-five women in WL conservative treatment (BMI ≥ 25 kg/m2) were measured (for about 3 months in between 2016 and 2018) by actigraphy.

Results: We observed a difference in time of acrophase ( = 0.

Methods for automatic detection of artifacts in microelectrode recordings.

Background: Extracellular microelectrode recording (MER) is a prominent technique for studies of extracellular single-unit neuronal activity. In order to achieve robust results in more complex analysis pipelines, it is necessary to have high quality input data with a low amount of artifacts. We show that noise (mainly electromagnetic interference and motion artifacts) may affect more than 25% of the recording length in a clinical MER database.

Evaluation of diabetes mellitus compensation after one year of using Mobiab system.

This paper shows how the Mobiab system is useful for patients and which features are usually used. 18 users of the Mobiab system have been chosen. The data for this study was collected since February 2015 to February 2016.

Optimization of Parkinson Disease treatment combining anti-Parkinson drugs and deep brain stimulation using patient diaries.

The number of patients suffering from Parkinson's disease is increasing rapidly due to population aging. While traditional medications-based palliative therapy is successful in early stages, deep brain stimulation (DBS) may be used as an alternative treatment in later stages. After DBS implantation, the therapy typically consists of electrical stimulation and reduced medication.

Supervised segmentation of microelectrode recording artifacts using power spectral density.

Appropriate detection of clean signal segments in extracellular microelectrode recordings (MER) is vital for maintaining high signal-to-noise ratio in MER studies. Existing alternatives to manual signal inspection are based on unsupervised change-point detection. We present a method of supervised MER artifact classification, based on power spectral density (PSD) and evaluate its performance on a database of 95 labelled MER signals.