Feature group partitioning: an approach for depression severity prediction with class balancing using machine learning algorithms.

In contemporary society, depression has emerged as a prominent mental disorder that exhibits exponential growth and exerts a substantial influence on premature mortality. Although numerous research applied machine learning methods to forecast signs of depression. Nevertheless, only a limited number of research have taken into account the severity level as a multiclass variable.

Validation of Smartphone Accelerometry for the Evaluation of Sit-To-Stand Performance and Lower-Extremity Function in Older Adults.

This study tested the concurrent and construct validity of smartphone accelerometry measurement of sit-to-stand (STS) performance in individuals aged 65-89 years. Normal and fast STS times were recorded by smartphone accelerometer, force plate, and video motion systems concurrently, and isokinetic knee extension power and STS whole-body power were obtained. Normal and fast speed STS times from a smartphone accelerometer agreed closely with force plate and motion system methods (mean difference = 0.

Stimulus-Driven Retinal Intrinsic Signal Optical Imaging in Mouse Demonstrates a Dominant Rod-Driven Component.

Purpose: The primary hypotheses tested are that (1) there exist stimulus-driven intrinsic optical signals in the mouse retina similar to those previously observed in other species, and (2) these optical signals require an intact rod photoreceptor phototransduction cascade.

Methods: We used 38 wild-type C57BL6J mice and 18 genetic knockout Gnat1-/- mice to study the light-evoked retinal intrinsic response. A custom mouse fundus camera delivered visual stimuli and collected mouse retinal imaging data of changes in retinal reflectance for further analysis.

Caregiver perspectives on a smart home-based socially assistive robot for individuals with Alzheimer's disease and related dementia.

: Innovative assistive technology can address aging-in-place and caregiving needs of individuals with Alzheimer's disease and related dementia (ADRD). The purpose of this study was to beta-test a novel socially assistive robot (SAR) with a cohort of ADRD caregivers and gather their perspectives on its potential integration in the home context.: The SAR involved a programmable research robot linked with commercially available Internet of things sensors to receive and respond to care recipient's behaviour.

A learning-based agent for home neurorehabilitation.

This paper presents the iterative development of an artificially intelligent system to promote home-based neurorehabilitation. Although proper, structured practice of rehabilitation exercises at home is the key to successful recovery of motor functions, there is no home-program out there which can monitor a patient's exercise-related activities and provide corrective feedback in real time. To this end, we designed a Learning from Demonstration (LfD) based home-rehabilitation framework that combines advanced robot learning algorithms with commercially available wearable technologies.

Robots to assist daily activities: views of older adults with Alzheimer's disease and their caregivers.

Background: Robots have the potential to both enable older adults with dementia to perform daily activities with greater independence, and provide support to caregivers. This study explored perspectives of older adults with Alzheimer's disease (AD) and their caregivers on robots that provide stepwise prompting to complete activities in the home.

Methods: Ten dyads participated: Older adults with mild-to-moderate AD and difficulty completing activity steps, and their family caregivers.

Performance of daily activities by older adults with dementia: the role of an assistive robot.

Older adults with cognitive impairment often have difficulties in remembering the proper sequence of activities of daily living (ADLs) or how to use the tools necessary to perform ADLs. They, therefore, require reminders in a timely fashion while performing ADLs. This is a very stressful situation for the caregivers of people with dementia.

A probabilistic model of overt visual attention for cognitive robots.

Visual attention is one of the major requirements for a robot to serve as a cognitive companion for human. The robotic visual attention is mostly concerned with overt attention which accompanies head and eye movements of a robot. In this case, each movement of the camera head triggers a number of events, namely transformation of the camera and the image coordinate systems, change of content of the visual field, and partial appearance of the stimuli.

Macronutrient intake and glycemic control in a population-based sample of American Indians with diabetes: the Strong Heart Study.

Background: Little research has explored the association of macronutrient intake and glycated hemoglobin (HbA(1c)) in adults with diabetes.

Objective: The objective of the study was to examine the cross-sectional association between macronutrient intake and HbA(1c) in diabetic American Indians.

Design: A total of 1284 participants aged 47-80 y who had diabetes for >or=1 y at the second examination (1993-1995) of the Strong Heart Study were included in this study.

Albuminuria within the "normal" range and risk of cardiovascular disease and death in American Indians: the Strong Heart Study.

Background: "Normal" albuminuria has been defined as urinary albumin-creatinine ratio (UACR) less than 30 mg/g (3.4 mg/mmol). Whether higher UACR within this range independently predicts cardiovascular disease (CVD) and CVD death is uncertain.

Type 2 diabetes and impaired fasting glucose in American Indians aged 5-40 years: the Cherokee diabetes study.

Purpose: To estimate the prevalence of type 2 diabetes and impaired fasting glucose (IFG) and to study several potential risk factors for type 2 diabetes among Oklahoma Cherokees aged 5 to 40 years.

Methods: A random sample of 2205 members of the Cherokee Nation of Oklahoma aged 5 to 40 years was recruited. Demographic, clinical, and laboratory data were collected.