Periodic mobile application (eMOM) with self-tracking of glucose and lifestyle improves treatment of diet-controlled gestational diabetes without human guidance: a randomized controlled trial.

Background: Digitalization with minimal human resources could support self-management among women with gestational diabetes and improve maternal and neonatal outcomes.

Objective: This study aimed to investigate if a periodic mobile application (eMOM) with wearable sensors improves maternal and neonatal outcomes among women with diet-controlled gestational diabetes without additional guidance from healthcare personnel.

Study Design: Women with gestational diabetes were randomly assigned in a 1:1 ratio at 24 to 28 weeks' gestation to the intervention or the control arm.

The 2023 wearable photoplethysmography roadmap.

Photoplethysmography is a key sensing technology which is used in wearable devices such as smartwatches and fitness trackers. Currently, photoplethysmography sensors are used to monitor physiological parameters including heart rate and heart rhythm, and to track activities like sleep and exercise. Yet, wearable photoplethysmography has potential to provide much more information on health and wellbeing, which could inform clinical decision making.

Comprehensive self-tracking of blood glucose and lifestyle with a mobile application in the management of gestational diabetes: a study protocol for a randomised controlled trial (eMOM GDM study).

Introduction: Gestational diabetes (GDM) causes various adverse short-term and long-term consequences for the mother and child, and its incidence is increasing globally. So far, the most promising digital health interventions for GDM management have involved healthcare professionals to provide guidance and feedback. The principal aim of this study is to evaluate the effects of comprehensive and real-time self-tracking with eMOM GDM mobile application (app) on glucose levels in women with GDM, and more broadly, on different other maternal and neonatal outcomes.

Comparison of Heart Rate Monitoring Accuracy between Chest Strap and Vest during Physical Training and Implications on Training Decisions.

Heart rate (HR) and heart rate variability (HRV) based physiological metrics such as Excess Post-exercise Oxygen Consumption (EPOC), Energy Expenditure (EE), and Training Impulse (TRIMP) are widely utilized in coaching to monitor and optimize an athlete's training load. Chest straps, and recently also dry electrodes integrated to special sports vests, are used to monitor HR during sports. Mechanical design, placement of electrodes, and ergonomics of the sensor affect the measured signal quality and artefacts.

Glial cell line-derived neurotrophic factor receptor Rearranged during transfection agonist supports dopamine neurons in Vitro and enhances dopamine release In Vivo.

Background: Motor symptoms of Parkinson's disease (PD) are caused by degeneration and progressive loss of nigrostriatal dopamine neurons. Currently, no cure for this disease is available. Existing drugs alleviate PD symptoms but fail to halt neurodegeneration.

Health timeline: an insight-based study of a timeline visualization of clinical data.

Background: The increasing complexity and volume of clinical data poses a challenge in the decision-making process. Data visualizations can assist in this process by speeding up the time required to analyze and understand clinical data. Even though empirical experiments show that visualizations facilitate clinical data understanding, a consistent method to assess their effectiveness is still missing.

Exploring Associations Between the Self-Reported Values, Well-Being, and Health Behaviors of Finnish Citizens: Cross-Sectional Analysis of More Than 100,000 Web-Survey Responses.

Background: Understanding the relationship between personal values, well-being, and health-related behavior could facilitate the development of engaging, effective digital interventions for promoting well-being and the healthy lifestyles of citizens. Although the associations between well-being and values have been quite extensively studied, the knowledge about the relationship between health behaviors and values is less comprehensive.

Objective: The aim of this study was to assess retrospectively the associations between self-reported values and commitment to values combined with self-reported well-being and health behaviors from a large cross-sectional dataset.

The Accuracy of Atrial Fibrillation Detection from Wrist Photoplethysmography. A Study on Post-Operative Patients.

Atrial fibrillation (AF) is the most common type of cardiac arrhythmia. Although not life-threatening itself, AF significantly increases the risk of stroke and myocardial infarction. Current tools available for screening and monitoring of AF are inadequate and an unobtrusive alternative, suitable for long-term use, is needed.

Monitoring of heart rate and inter-beat intervals with wrist plethysmography in patients with atrial fibrillation.

Objective: Atrial fibrillation (AF) causes marked risk for patients, while silent fibrillation may remain unnoticed if not suspected and screened. Development of comfortable yet accurate beat-to-beat heart rate (HR) monitoring with good AF detection sensitivity would facilitate screening and improve treatment. The purpose of this study was to evaluate whether a wrist-worn photoplethysmography (PPG) device can be used to monitor beat-to-beat HR accurately during post-operative treatment in patients suffering from AF and whether wrist-PPG can be used to distinguish AF from sinus rhythm (SR).

Acute Effect of Alcohol Intake on Cardiovascular Autonomic Regulation During the First Hours of Sleep in a Large Real-World Sample of Finnish Employees: Observational Study.

Background: Sleep is fundamental for good health, and poor sleep has been associated with negative health outcomes. Alcohol consumption is a universal health behavior associated with poor sleep. In controlled laboratory studies, alcohol intake has been shown to alter physiology and disturb sleep homeostasis and architecture.

An Activity Recognition Framework Deploying the Random Forest Classifier and A Single Optical Heart Rate Monitoring and Triaxial AccelerometerWrist-Band.

Wrist-worn sensors have better compliance for activity monitoring compared to hip, waist, ankle or chest positions. However, wrist-worn activity monitoring is challenging due to the wide degree of freedom for the hand movements, as well as similarity of hand movements in different activities such as varying intensities of cycling. To strengthen the ability of wrist-worn sensors in detecting human activities more accurately, motion signals can be complemented by physiological signals such as optical heart rate (HR) based on photoplethysmography.

Estimating Heart Rate, Energy Expenditure, and Physical Performance With a Wrist Photoplethysmographic Device During Running.

Background: Wearable sensors enable long-term monitoring of health and wellbeing indicators. An objective evaluation of sensors' accuracy is important, especially for their use in health care.

Objective: The aim of this study was to use a wrist-worn optical heart rate (OHR) device to estimate heart rate (HR), energy expenditure (EE), and maximal oxygen intake capacity (VO) during running and to evaluate the accuracy of the estimated parameters (HR, EE, and VO) against golden reference methods.

Seasonal weight variation patterns in seven countries located in northern and southern hemispheres.

The digital revolution of information and technology in late 20th century has led to emergence of devices that help people monitor their weight in a long-term manner. Investigation of population-level variations of body mass using smart connected weight scales enabled the health coaches acquire deeper insights about the models of people's behavior as a function of time. Typically, body mass varies when the seasons change.

Towards 24/7 continuous heart rate monitoring.

Heart rate (HR) and HR variability (HRV) carry rich information about physical activity, mental and physical load, physiological status, and health of an individual. When combined with activity monitoring and personalized physiological modelling, HR/HRV monitoring may be used for monitoring of complex behaviors and impact of behaviors and external factors on the current physiological status of an individual. Optical HR monitoring (OHR) from wrist provides a comfortable and unobtrusive method for HR/HRV monitoring and is better adhered by users than traditional ECG electrodes or chest straps.

Procedures for Evaluating the Adequacy of Anesthesia.

Assessing adequacy of anesthesia requires evaluation of its components: hypnosis, analgesia, and neuromuscular transmission. In order to do this, many methods have been developed that process signals representing different modalities. Assessment of hypnosis requires cortical measures of the central nervous system (CNS); methods that assess analgesia concentrate on subcortical and spinal levels of the CNS; and neuromuscular transmission is a peripheral phenomenon.

Association between Continuous Wearable Activity Monitoring and Self-Reported Functioning in Assisted Living Facility and Nursing Home Residents.

Background: Physical functioning is a key factor in independent living, and its preclinical state assessment and monitoring during the subject's normal life would be beneficial.

Objectives: The aim of the study is to analyse associations between ambulatory measured physical activity behaviour and sleep patterns (wrist actigraphy) and self-reported difficulties in performing activities of daily living. Participants, setting and design: 36 residents in assisted living facilities and nursing homes (average age=80.

Physical Activity: Absolute Intensity versus Relative-to-Fitness-Level Volumes.

Purpose: This study aimed to investigate in a real-life setting how moderate- and vigorous-intensity physical activity (PA) volumes differ according to absolute intensity recommendation and relative to individual fitness level by sex, age, and body mass index.

Methods: A total of 23,224 Finnish employees (10,201 men and 13,023 women; ages 18-65 yr; body mass index = 18.5-40.

Evaluation of the beat-to-beat detection accuracy of PulseOn wearable optical heart rate monitor.

Heart rate variability (HRV) provides significant information about the health status of an individual. Optical heart rate monitoring is a comfortable alternative to ECG based heart rate monitoring. However, most available optical heart rate monitoring devices do not supply beat-to-beat detection accuracy required by proper HRV analysis.

Exploratory analysis of associations between individual lifestyles and heart rate variability -based recovery during sleep.

Sleep is the most important period for recovering from daily stress and load. Assessment of the stress recovery during sleep is therefore, an important metric for care and quality of life. Heart rate variability (HRV) is a non-invasive marker of autonomic nervous system (ANS) activity, and HRV-based methods can be used to assess physiological recovery, characterized by parasympathetic domination of the ANS.

Time-series modeling of long-term weight self-monitoring data.

Long-term self-monitoring of weight is beneficial for weight maintenance, especially after weight loss. Connected weight scales accumulate time series information over long term and hence enable time series analysis of the data. The analysis can reveal individual patterns, provide more sensitive detection of significant weight trends, and enable more accurate and timely prediction of weight outcomes.

Evaluation of accuracy and reliability of PulseOn optical heart rate monitoring device.

PulseOn is a wrist-worn optical heart rate (HR) monitor based on photoplethysmography. It utilizes multi-wavelength technology and optimized sensor geometry to monitor blood flow at different depths of skin tissue, and it dynamically adapts to an optimal measurement depth in different conditions. Movement artefacts are reduced by adaptive movement-cancellation algorithms and optimized mechanics, which stabilize the sensor-to-skin contact.

Behavioral Informatics and Computational Modeling in Support of Proactive Health Management and Care.

Health-related behaviors are among the most significant determinants of health and quality of life. Improving health behavior is an effective way to enhance health outcomes and mitigate the escalating challenges arising from an increasingly aging population and the proliferation of chronic diseases. Although it has been difficult to obtain lasting improvements in health behaviors on a wide scale, advances at the intersection of technology and behavioral science may provide the tools to address this challenge.

W2E--Wellness Warehouse Engine for Semantic Interoperability of Consumer Health Data.

Novel health monitoring devices and applications allow consumers easy and ubiquitous ways to monitor their health status. However, technologies from different providers lack both technical and semantic interoperability and hence the resulting health data are often deeply tied to a specific service, which is limiting its reusability and utilization in different services. We have designed a Wellness Warehouse Engine (W2E) that bridges this gap and enables seamless exchange of data between different services.