AIMC Topic: Actigraphy

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Functional cortical localization of tongue movements using corticokinematic coherence with a deep learning-assisted motion capture system.

Scientific reports Jan 10, 2022
Corticokinematic coherence (CKC) between magnetoencephalographic and movement signals using an accelerometer is useful for the functional localization of the primary sensorimotor cortex (SM1). However, it is difficult to determine the tongue CKC beca...
Time Factors Image Processing, Computer-Assisted Magnetic Resonance Imaging Brain Mapping Biomechanical Phenomena Male Deep Learning Actigraphy Movement Magnetoencephalography Sensorimotor Cortex Predictive Value of Tests Tongue Video Recording Fingers Humans Female Young Adult Adult
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Deep-Learning Approach to Predict Survival Outcomes Using Wearable Actigraphy Device Among End-Stage Cancer Patients.

Frontiers in public health Dec 9, 2021
Survival prediction is highly valued in end-of-life care clinical practice, and patient performance status evaluation stands as a predominant component in survival prognostication. While current performance status evaluation tools are limited to thei...
Deep Learning Wearable Electronic Devices Hospital Mortality Actigraphy Humans Neoplasms
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Digital phenotyping of sleep patterns among heterogenous samples of Latinx adults using unsupervised learning.

Sleep medicine Jul 19, 2021
OBJECTIVE: This study aimed to identify sleep disturbance subtypes ("phenotypes") among Latinx adults based on objective sleep data using a flexible unsupervised machine learning technique.
Unsupervised Machine Learning Sleep Actigraphy Polysomnography Young Adult Adult Cross-Sectional Studies Middle Aged Humans Aged
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A classification approach to estimating human circadian phase under circadian alignment from actigraphy and photometry data.

Journal of pineal research Jun 20, 2021
The time of dim light melatonin onset (DLMO) is the gold standard for circadian phase assessment in humans, but collection of samples for DLMO is time and resource-intensive. Numerous studies have attempted to estimate circadian phase from actigraphy...
Male Circadian Rhythm Melatonin Actigraphy Humans Neural Networks, Computer Female Adult Photometry
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Deep Neural Network Sleep Scoring Using Combined Motion and Heart Rate Variability Data.

Sensors (Basel, Switzerland) Dec 23, 2020
Performance of wrist actigraphy in assessing sleep not only depends on the sensor technology of the actigraph hardware but also on the attributes of the interpretative algorithm (IA). The objective of our research was to improve assessment of sleep ...
Polysomnography Humans Neural Networks, Computer Female Male Heart Rate Sleep Actigraphy
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Machine learning from wristband sensor data for wearable, noninvasive seizure forecasting.

Epilepsia Oct 11, 2020
OBJECTIVE: Seizure forecasting may provide patients with timely warnings to adapt their daily activities and help clinicians deliver more objective, personalized treatments. Although recent work has convincingly demonstrated that seizure risk assessm...
Monitoring, Ambulatory Humans Body Temperature Machine Learning Actigraphy Child Forecasting Pulse Seizures Male Young Adult Wrist Adolescent Wearable Electronic Devices Child, Preschool
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Deep Learning Approach for Imputation of Missing Values in Actigraphy Data: Algorithm Development Study.

JMIR mHealth and uHealth Jul 23, 2020
BACKGROUND: Data collected by an actigraphy device worn on the wrist or waist can provide objective measurements for studies related to physical activity; however, some data may contain intervals where values are missing. In previous studies, statist...
Humans Male Algorithms Middle Aged Female Deep Learning Adult Actigraphy
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Application of deep learning to improve sleep scoring of wrist actigraphy.

Sleep medicine May 15, 2020
BACKGROUND: Estimation of sleep parameters by wrist actigraphy is highly dependent on performance of the interpretative algorithm (IA) that converts movement data into sleep/wake scores.
Wrist Sleep Actigraphy Female Humans Polysomnography Adult Deep Learning
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Predicting polysomnographic severity thresholds in children using machine learning.

Pediatric research May 9, 2020
BACKGROUND: Approximately 500,000 children undergo tonsillectomy and adenoidectomy (T&A) annually for treatment of obstructive sleep disordered breathing (oSDB). Although polysomnography is beneficial for preoperative risk stratification in these chi...
Risk Actigraphy Hypersensitivity Polysomnography Oximetry Adenoidectomy Asthma Humans Signal Processing, Computer-Assisted Male Machine Learning Sleep Apnea Syndromes Surveys and Questionnaires Algorithms Sleep Apnea, Obstructive Child Monitoring, Physiologic Female Anthropometry Decision Making Tonsillectomy
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Performance Analysis of Boosting Classifiers in Recognizing Activities of Daily Living.

International journal of environmental research and public health Feb 8, 2020
Physical activity is essential for physical and mental health, and its absence is highly associated with severe health conditions and disorders. Therefore, tracking activities of daily living can help promote quality of life. Wearable sensors in this...
Quality of Life Reproducibility of Results Humans Exercise Supervised Machine Learning Smartphone Activities of Daily Living Algorithms Adult Actigraphy Female Male Middle Aged
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