AIMC Topic: Actigraphy

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Exploring Factors Related to Social Isolation Among Older Adults in the Predementia Stage Using Ecological Momentary Assessments and Actigraphy: Machine Learning Approach.

Journal of medical Internet research
BACKGROUND: As the global population ages, the economic burden of dementia continues to rise. Social isolation-which includes limited social interaction and feelings of loneliness-negatively affects cognitive function and is a significant risk factor...

The two ends of the spectrum: comparing chronic schizophrenia and premorbid latent schizotypy by actigraphy.

BMC psychiatry
Motor activity alterations are key symptoms of psychiatric disorders like schizophrenia. Actigraphy, a non-invasive monitoring method, shows promise in early identification. This study characterizes Positive Schizotypy Factor (PSF) and Chronic Schizo...

Apnea detection using wrist actigraphy in patients with heterogeneous sleep disorders.

Scientific reports
Obstructive sleep apnea (OSA) and related hypoxia are well-established cardiovascular and neurocognitive risk factors. Current multi-sensor diagnostic approaches are intrusive and prone to misdiagnosis when simplified. This study introduces an enhanc...

Actigraphy against 32-hour polysomnography in patients with suspected idiopathic hypersomnia.

Journal of sleep research
Actigraphy, a tool known for investigating sleep-wake patterns at home, lacks scientific validation in hypersomnolent subjects. We aim to validate an actigraphy-based sleep-wake prediction algorithm against 32-h continuous polysomnography in patients...

Performance evaluation of a machine learning-based methodology using dynamical features to detect nonwear intervals in actigraphy data in a free-living setting.

Sleep health
GOAL AND AIMS: One challenge using wearable sensors is nonwear time. Without a nonwear (e.g., capacitive) sensor, actigraphy data quality can be biased by subjective determinations confounding sleep/wake classification. We developed and evaluated a m...

Virtual reality-assisted prediction of adult ADHD based on eye tracking, EEG, actigraphy and behavioral indices: a machine learning analysis of independent training and test samples.

Translational psychiatry
Given the heterogeneous nature of attention-deficit/hyperactivity disorder (ADHD) and the absence of established biomarkers, accurate diagnosis and effective treatment remain a challenge in clinical practice. This study investigates the predictive ut...

Automated Sleep Detection in Movement Disorders Using Deep Brain Stimulation and Machine Learning.

Movement disorders : official journal of the Movement Disorder Society
BACKGROUND: Automated sleep detection in movement disorders may allow monitoring sleep, potentially guiding adaptive deep brain stimulation (DBS).

Quantifying Nocturnal Scratch in Atopic Dermatitis: A Machine Learning Approach Using Digital Wrist Actigraphy.

Sensors (Basel, Switzerland)
Nocturnal scratching substantially impairs the quality of life in individuals with skin conditions such as atopic dermatitis (AD). Current clinical measurements of scratch rely on patient-reported outcomes (PROs) on itch over the last 24 h. Such meas...

A robot intervention for adults with ADHD and insomnia-A mixed-method proof-of-concept study.

PloS one
OBJECTIVE: To investigate individual effects of a three-week sleep robot intervention in adults with ADHD and insomnia, and to explore participants' experiences with the intervention.