Activity Assay:Article Title: Wearables research for continuous monitoring of patient outcomes: A scoping review
Article Snippet: [ ] , Carreiro et al., 2020 , USA , Observational , No , 31 , 32 , Substance use disorder/ electrodermal activity, skin temperature, acceleration, heart rate , 4 days , E4 wearable sensor , Device parameters associated with patient-reported stress and craving... .. [ ] , Knight et al., 2018 , Australia , Prospective, cohort, observational , No , 53 , 21 , Depression, anxiety/ daily activity duration , 8 months , Fitbit, Garmin , Correlations observed between anxiety and emotional volatility scores and daily activity over 45 days of measurement.. .. [ ] , Lahti et al., 2021 , USA , Observational , No , 40 , 40 , Schizophrenia/ sleep-wake, activity count, light exposure, step count , 4 months , Philips Actiwatch, Garmin Vivofit wristband , Wearable data and psychotic symptoms were correlated..
Article Title: The Potential of Wearable, Modular Devices in Monitoring Functional Clinical Metrics in Patients Suffering from Chronic Pain.
Article Snippet: Purpose of Review This review assesses the role of wearable technologies in pain management, emphasizing their capability to transcend subjective pain evaluations with objective functional outcome tracking.. We explore the types and veracity of health metrics wearable devices track, illustrating how this technological evolution can significantly enhance patient care in the context of chronic pain prevention and management.. Recent Findings The advancements in modular wearable technology offer new avenues to track a variety of health outcomes, including aerobic capacity, physical activity, stress, and sleep quality.
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Article Title: Devices and methods for treating stress and improving alertness using electrical stimulation
Article Snippet: In some embodiments, the peripheral device(s) 1010 include a fitness-monitoring device, such as a Fitbit, Apple Watch, or Garmin Smartwatch.
Comparison:Article Title: Digital Phenotyping of Mental and Physical Conditions: Remote Monitoring of Patients Through RADAR-Base Platform.
Article Snippet: .. Project and disease area Size n Enrolled, n Devices/data types Main objectives Autism 500 300 (ongoing) Empatica E4, Fitbit, phone sensors, questionnaires Biology of autism to tailor treatments and develop new therapies and medicines BigData@Heart Atrial fibrillation 160 160 Phone sensors, questionnaires Comparison of 2 strategies of rate control, based either on initial treatment with digoxin or β-blockers DynaMOREh Mental health —i — Phone sensors, questionnaires Developing an in-silico model of stress resilience CONVALESCENCE Long-term effects of COVID-19 800 363 (ongoing) Garmin Vivoactive, phone sensors, questionnaires Characterization, determinants, mechanisms, and consequences of the long-term effects of COVID-19 COVID-Collab COVID-19 15,000 17,667 Fitbit, questionnaires Behavior and physical and mental health occur in response to COVID-19 infection, persistent symptoms, and the pandemic in general RALPMHj Lung disease 60 60 Garmin Vivoactive, phone sensors, Questionnaires Feasibility of remote-monitoring technologies for high-burden pulmonary disorders EDIFY Eating disorder 500 10 (ongoing) Oura Ring, phone sensors, questionnaires Delineating illness and recovery trajectories to inform personalized prevention and early intervention in young people UNFOLD Psychosis 50 — Questionnaires To characterize the processes involved in developing an identity as a person in recovery Jovens na Pandemia & MAAY Study Depression 280 — Phone sensors, question- naires Remotely monitor behavioral and symptom changes associated with behavioral interventions in children and adolescents aRADAR-CNS: Remote Assessment of Disease and Relapse—Central Nervous System. bAttention-Deficit/Hyperactivity Disorder Remote Technology Study of Cardiometabolic Risk Factors and Medication Adherence. cART: ADHD Remote Technology. dADHD: attention-deficit/hyperactivity disorder eRADAR-AD: Remote Assessment of Disease and Relapse–Alzheimer Disease. fAD: Alzheimer disease. gAIMS-2-TRIALS: Autism Innovative Medicine Studies–2–Trials. hDynaMORE: Dynamic Modelling of Resilience. iNot available. jRALPMH: Remote Assessment of Lung Disease and Impact on Physical and Mental Health. ..
Control:Article Title: Digital Phenotyping of Mental and Physical Conditions: Remote Monitoring of Patients Through RADAR-Base Platform.
Article Snippet: .. Project and disease area Size n Enrolled, n Devices/data types Main objectives Autism 500 300 (ongoing) Empatica E4, Fitbit, phone sensors, questionnaires Biology of autism to tailor treatments and develop new therapies and medicines BigData@Heart Atrial fibrillation 160 160 Phone sensors, questionnaires Comparison of 2 strategies of rate control, based either on initial treatment with digoxin or β-blockers DynaMOREh Mental health —i — Phone sensors, questionnaires Developing an in-silico model of stress resilience CONVALESCENCE Long-term effects of COVID-19 800 363 (ongoing) Garmin Vivoactive, phone sensors, questionnaires Characterization, determinants, mechanisms, and consequences of the long-term effects of COVID-19 COVID-Collab COVID-19 15,000 17,667 Fitbit, questionnaires Behavior and physical and mental health occur in response to COVID-19 infection, persistent symptoms, and the pandemic in general RALPMHj Lung disease 60 60 Garmin Vivoactive, phone sensors, Questionnaires Feasibility of remote-monitoring technologies for high-burden pulmonary disorders EDIFY Eating disorder 500 10 (ongoing) Oura Ring, phone sensors, questionnaires Delineating illness and recovery trajectories to inform personalized prevention and early intervention in young people UNFOLD Psychosis 50 — Questionnaires To characterize the processes involved in developing an identity as a person in recovery Jovens na Pandemia & MAAY Study Depression 280 — Phone sensors, question- naires Remotely monitor behavioral and symptom changes associated with behavioral interventions in children and adolescents aRADAR-CNS: Remote Assessment of Disease and Relapse—Central Nervous System. bAttention-Deficit/Hyperactivity Disorder Remote Technology Study of Cardiometabolic Risk Factors and Medication Adherence. cART: ADHD Remote Technology. dADHD: attention-deficit/hyperactivity disorder eRADAR-AD: Remote Assessment of Disease and Relapse–Alzheimer Disease. fAD: Alzheimer disease. gAIMS-2-TRIALS: Autism Innovative Medicine Studies–2–Trials. hDynaMORE: Dynamic Modelling of Resilience. iNot available. jRALPMH: Remote Assessment of Lung Disease and Impact on Physical and Mental Health. ..
Infection:Article Title: Digital Phenotyping of Mental and Physical Conditions: Remote Monitoring of Patients Through RADAR-Base Platform.
Article Snippet: .. Project and disease area Size n Enrolled, n Devices/data types Main objectives Autism 500 300 (ongoing) Empatica E4, Fitbit, phone sensors, questionnaires Biology of autism to tailor treatments and develop new therapies and medicines BigData@Heart Atrial fibrillation 160 160 Phone sensors, questionnaires Comparison of 2 strategies of rate control, based either on initial treatment with digoxin or β-blockers DynaMOREh Mental health —i — Phone sensors, questionnaires Developing an in-silico model of stress resilience CONVALESCENCE Long-term effects of COVID-19 800 363 (ongoing) Garmin Vivoactive, phone sensors, questionnaires Characterization, determinants, mechanisms, and consequences of the long-term effects of COVID-19 COVID-Collab COVID-19 15,000 17,667 Fitbit, questionnaires Behavior and physical and mental health occur in response to COVID-19 infection, persistent symptoms, and the pandemic in general RALPMHj Lung disease 60 60 Garmin Vivoactive, phone sensors, Questionnaires Feasibility of remote-monitoring technologies for high-burden pulmonary disorders EDIFY Eating disorder 500 10 (ongoing) Oura Ring, phone sensors, questionnaires Delineating illness and recovery trajectories to inform personalized prevention and early intervention in young people UNFOLD Psychosis 50 — Questionnaires To characterize the processes involved in developing an identity as a person in recovery Jovens na Pandemia & MAAY Study Depression 280 — Phone sensors, question- naires Remotely monitor behavioral and symptom changes associated with behavioral interventions in children and adolescents aRADAR-CNS: Remote Assessment of Disease and Relapse—Central Nervous System. bAttention-Deficit/Hyperactivity Disorder Remote Technology Study of Cardiometabolic Risk Factors and Medication Adherence. cART: ADHD Remote Technology. dADHD: attention-deficit/hyperactivity disorder eRADAR-AD: Remote Assessment of Disease and Relapse–Alzheimer Disease. fAD: Alzheimer disease. gAIMS-2-TRIALS: Autism Innovative Medicine Studies–2–Trials. hDynaMORE: Dynamic Modelling of Resilience. iNot available. jRALPMH: Remote Assessment of Lung Disease and Impact on Physical and Mental Health. ..
Sampling:
Expressing:Article Title: Use of physiological signals, behavioral data, and processing algorithms in electronic devices and mobile applications for diagnosing depression, anxiety, and stress
Article Snippet: .. Smartwatches and fitness bands, such as Fitbit and Garmin Vivosmart, are notable for HR monitoring, achieving accuracy rates between 85% and 95%, though they are susceptible to motion artifacts., , , Devices like Empatica E4, used for EDA, achieve accuracy levels above 90%, though their comfort level restricts prolonged use., , Portable EEG devices such as Emotiv EPOC attain accuracy rates between 80% and 92%, but they are highly sensitive to external noise and require controlled environments., On the behavioral analysis side, applications like StudentLife demonstrate an average accuracy of 85% in detecting phone usage patterns and mobility, though they depend on the quality of mobile phone sensors., Cameras such as the Logitech C1000E achieve accuracy rates between 80% and 90% for facial expression analysis but face challenges related to privacy and positioning., VR devices like HTC Vive Pro Eye offer accuracy levels above 90% in experimental settings, though their high cost and technical requirements limit their implementation., The reviewed studies investigating the diagnosis of depression, anxiety, and stress through electronic devices have led to significant advancements but also highlight several areas where further research is needed. ..
Biomarker Discovery:Article Title: Use of physiological signals, behavioral data, and processing algorithms in electronic devices and mobile applications for diagnosing depression, anxiety, and stress
Article Snippet: .. Smartwatches and fitness bands, such as Fitbit and Garmin Vivosmart, are notable for HR monitoring, achieving accuracy rates between 85% and 95%, though they are susceptible to motion artifacts., , , Devices like Empatica E4, used for EDA, achieve accuracy levels above 90%, though their comfort level restricts prolonged use., , Portable EEG devices such as Emotiv EPOC attain accuracy rates between 80% and 92%, but they are highly sensitive to external noise and require controlled environments., On the behavioral analysis side, applications like StudentLife demonstrate an average accuracy of 85% in detecting phone usage patterns and mobility, though they depend on the quality of mobile phone sensors., Cameras such as the Logitech C1000E achieve accuracy rates between 80% and 90% for facial expression analysis but face challenges related to privacy and positioning., VR devices like HTC Vive Pro Eye offer accuracy levels above 90% in experimental settings, though their high cost and technical requirements limit their implementation., The reviewed studies investigating the diagnosis of depression, anxiety, and stress through electronic devices have led to significant advancements but also highlight several areas where further research is needed. ..
Derivative Assay:Article Title: Incorporating a Physical Activity mHealth Tool Into a Multidisciplinary Clinical Weight Management Service in England: Service Evaluation of Steps4Health.
Article Snippet: Louisa Y.. Herring, Joseph Henson, Martha Thomas, Ehtasham Ahmad, Christopher Brough, Julia Burdon, Charlotte L. Edwardson, Michelle Hadjiconstantinou, Alison Northern, David Webb, Hannah Young, Lucina Wilde, Melanie J. Davies, and Thomas Yates Leicester Diabetes Centre, University Hospitals of Leicester NHS Trust, Leicester, United Kingdom; Leicester Biomedical Research Centre, University of Leicester and University Hospitals of Leicester NHS Trust, Leicester, United Kingdom; Diabetes Research Centre, College of Life Sciences, University of Leicester, Leicester, United Kingdom
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