The Development of a Wearable-Based System for Detecting Shaken Baby Syndrome Using Machine Learning Models.

Shaken Baby Syndrome (SBS) is one of the primary causes of fatal head trauma in infants and young children, occurring in about 33 per 100,000 infants annually in the U.S., with mortality rates being between 15% and 38%.

Using wearable sensors and machine learning to assess upper limb function in Huntington's disease.

Background: Huntington's disease, a neurodegenerative disorder, impairs both upper and lower limb function, typically assessed in clinical settings. However, wearable sensors offer the opportunity to monitor real-world data that complements clinical assessments, providing a more comprehensive understanding of disease symptoms.

Methods: In this study, we monitor upper limb function in individuals with Huntington's disease (HD, n = 16), prodromal HD (pHD, n = 7), and controls (CTR, n = 16) using a wrist-worn wearable sensor over a 7-day period.

At-home wearable-based monitoring predicts clinical measures and biological biomarkers of disease severity in Friedreich's Ataxia.

Background: Friedreich ataxia (FRDA) results in progressive impairment in gait, upper extremity coordination, and speech. Currently, these symptoms are assessed through expert examination at clinical visits. Such in-clinic assessments are time-consuming, subjective, of limited sensitivity, and provide only a limited perspective of the daily disability of patients.

Gastrocnemius electrical stimulation increases ankle dorsiflexion strength in patients with post-acute sequelae of SARS-COV-2 (PASC): a double-blind randomized controlled trial.

Post-Acute sequelae of SARS-CoV-2 (PASC) is a multisystem disorder causing persistent musculoskeletal deconditioning and reduced lower extremity strength. Electrical stimulation (E-Stim) to the gastrocnemius muscle can enhance strength outcomes by increasing the frequency of muscle fiber activation. We investigated its effect on individuals with PASC.

Digital assessment of speech in Huntington disease.

Background: Speech changes are an early symptom of Huntington disease (HD) and may occur prior to other motor and cognitive symptoms. Assessment of HD commonly uses clinician-rated outcome measures, which can be limited by observer variability and episodic administration. Speech symptoms are well suited for evaluation by digital measures which can enable sensitive, frequent, passive, and remote administration.

A deep learning wearable-based solution for continuous at-home monitoring of upper limb goal-directed movements.

Introduction: Monitoring upper limb function is crucial for tracking progress, assessing treatment effectiveness, and identifying potential problems or complications. Hand goal-directed movements (GDMs) are a crucial aspect of daily life, reflecting planned motor commands with hand trajectories towards specific target locations. Previous studies have shown that GDM tasks can detect early changes in upper limb function in neurodegenerative diseases and can be used to track disease progression over time.

Remote at-home wearable-based gait assessments in Progressive Supranuclear Palsy compared to Parkinson's Disease.

Background: Wearable sensors can differentiate Progressive Supranuclear Palsy (PSP) from Parkinson's Disease (PD) in laboratory settings but have not been tested in remote settings.

Objectives: To compare gait and balance in PSP and PD remotely using wearable-based assessments.

Methods: Participants with probable PSP or probable/clinically established PD with reliable caregivers, still able to ambulate 10 feet unassisted, were recruited, enrolled, and consented remotely and instructed by video conference to operate a study-specific tablet solution (BioDigit Home ™) and to wear three inertial sensors (LEGSys™, BioSensics LLC, Newton, MA USA) while performing the Timed Up and Go, 5 × sit-to-stand, and 2-min walk tests.

Utilizing speech analysis to differentiate progressive supranuclear palsy from Parkinson's disease.

Introduction: Distinguishing Parkinson's disease (PD) from Progressive supranuclear palsy (PSP) at early disease stages is important for clinical trial enrollment and clinical care/prognostication.

Methods: We recruited 21 participants with PSP(n = 11) or PD(n = 10) with reliable caregivers. Standardized passage reading, counting, and sustained phonation were recorded on the BioDigit Home tablet (BioSensics LLC, Newton, MA USA), and speech features from the assessments were analyzed using the BioDigit Speech platform (BioSensics LLC, Newton, MA USA).

Machine Learning-Based Aggression Detection in Children with ADHD Using Sensor-Based Physical Activity Monitoring.

Aggression in children is highly prevalent and can have devastating consequences, yet there is currently no objective method to track its frequency in daily life. This study aims to investigate the use of wearable-sensor-derived physical activity data and machine learning to objectively identify physical-aggressive incidents in children. Participants (n = 39) aged 7 to 16 years, with and without ADHD, wore a waist-worn activity monitor (ActiGraph, GT3X+) for up to one week, three times over 12 months, while demographic, anthropometric, and clinical data were collected.

Intradialytic plantar electrical nerve stimulation to improve mobility and plantar sensation among adults with diabetes undergoing hemodialysis: a randomized double-blind trial.

Background: Impaired mobility is a debilitating consequence of hemodialysis. We examined the efficacy of intradialytic-plantar-electrical-nerve-stimulation (iPENS) to promote mobility among diabetes patients undergoing hemodialysis..

Objective assessment of mobility among adults with diabetes and end-stage renal disease using walking aid: A cross-sectional cohort study.

Background: This cross-sectional study aimed to compare physical activity levels, plantar sensation, and fear of falling between individuals with diabetes undergoing hemodialysis, with or without walking aids.

Methods: Sixty-four participants were recruited, with 37 not using walking aids (age = 65.8 ± 0.

Using Wearable Sensors to Measure Goal Achievement in Older Veterans with Dementia.

Aligning treatment with patients' self-determined goals and health priorities is challenging in dementia care. Wearable-based remote health monitoring may facilitate determining the active participation of individuals with dementia towards achieving the determined goals. The present study aimed to demonstrate the feasibility of using wearables to assess healthcare goals set by older adults with cognitive impairment.

Objective Assessment of Upper-Extremity Motor Functions in Spinocerebellar Ataxia Using Wearable Sensors.

The study presents a novel approach to objectively assessing the upper-extremity motor symptoms in spinocerebellar ataxia (SCA) using data collected via a wearable sensor worn on the patient's wrist during upper-extremity tasks associated with the Assessment and Rating of Ataxia (SARA). First, we developed an algorithm for detecting/extracting the cycles of the finger-to-nose test (FNT). We extracted multiple features from the detected cycles and identified features and parameters correlated with the SARA scores.

Smart-Home Concept for Remote Monitoring of Instrumental Activities of Daily Living (IADL) in Older Adults with Cognitive Impairment: A Proof of Concept and Feasibility Study.

Assessment of instrumental activities of daily living (IADL) is essential for the diagnosis and staging of dementia. However, current IADL assessments are subjective and cannot be administered remotely. We proposed a smart-home design, called IADLSys, for remote monitoring of IADL.

Care4AD: A Technology-Driven Platform for Care Coordination and Management: Acceptability Study in Dementia.

Introduction: The technology-driven solution can reduce the caregiving burden; however, the needs of dementia caregiving are unique, and attitudes towards adopting technology from the perspectives of all the stakeholders involved in dementia caregiving are unclear. This study aims to assess the acceptability and feasibility of a technology-driven platform to facilitate care coordination platform, Care4AD, from the end-user perspective.

Methods: Care4AD includes three components: (1) Care4AD app: the app is used by caregivers to coordinate care, monitor physical activity, and schedule reminders; (2) Care4AD tablet: a smart tablet is used by the care recipient to display scheduled reminders; and (3) Care4AD tags: a series of wireless sensor tags attached to various objects of daily care to facilitate monitoring instrumental activities of daily living (IADL) and adherence to scheduled tasks.

The Application of Digital Frailty Screening to Triage Nonhealing and Complex Wounds.

Objective: We investigated the association between the complexity of diabetic foot ulcers (DFUs) and frailty.

Research Design And Methods: Individuals (n = 38) with Grade 2 Wagner DFU were classified into 3 groups based on the Society for Vascular Surgery risk-stratification for major limb amputation as Stage 1 at very low risk (n = 19), Stage 2 at low risk (n = 9), and Stage 3 to 4 at moderate-to-high risk (n = 10) of major limb amputation. Frailty status was objectively assessed using a validated digital frailty meter (FM).

Effect of concurrent transcranial direct current stimulation on instrumented timed up and go task performance in people with Parkinson's disease: A double-blind and cross-over study.

Transcranial direct current stimulation (tDCS) delivered to the dorsolateral prefrontal cortex (DLPFC) can improve mobility among people with Parkinson's disease (PD). Previous studies suggest that delivering tDCS during task performance might be beneficial. However, only a few studies explored the effect of combining tDCS with task.

Evaluation of Motor and Cognitive Performance in People with Parkinson's Disease Using Instrumented Trail-Making Test.

Introduction: Parkinson's disease (PD) progressively impairs motor and cognitive performance. The current tools to detect decline in motor and cognitive functioning are often impractical for busy clinics and home settings. To address the gap, we designed an instrumented trail-making task (iTMT) based on a wearable sensor (worn on the shin) with interactive game-based software installed on a tablet.

Transcranial direct current stimulation of dorsolateral prefrontal cortex improves dual-task gait performance in patients with Parkinson's disease: A double blind, sham-controlled study.

Background: Despite advances in pharmacological treatments and surgical processes, the problem of impaired dual-tasking persists in people with Parkinson's disease (PD). Recently, transcranial direct current stimulation (tDCS) applied to the dorsolateral prefrontal cortex (DLPFC) has shown the potential to improve dual-task walking.

Research Question: Can combining left DLPFC stimulation using tDCS with dual-task performance reduce the cost of dual-tasking in individuals with PD?

Methods: We conducted a sham-controlled, cross-over, and double-blind study to investigate the effect of combining tDCS with the dual-task walk and its sustained effects among people with PD.