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Activities of Daily Living

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Statistical machine learning of sleep and physical activity phenotypes from sensor data in 96,220 UK Biobank participants.

Scientific reports
Current public health guidelines on physical activity and sleep duration are limited by a reliance on subjective self-reported evidence. Using data from simple wrist-worn activity monitors, we developed a tailored machine learning model, using balanc...

Health management and pattern analysis of daily living activities of people with dementia using in-home sensors and machine learning techniques.

PloS one
The number of people diagnosed with dementia is expected to rise in the coming years. Given that there is currently no definite cure for dementia and the cost of care for this condition soars dramatically, slowing the decline and maintaining independ...

ESMAC BEST PAPER 2017: Using machine learning to overcome challenges in GMFCS level assignment.

Gait & posture
We used the random forest classifier to predict Gross Motor Function Classification System (GMFCS) levels I-IV from patient reported abilities recorded on the Gillette Functional Assessment Questionnaire (FAQ). The classifier exhibited outstanding ac...

Automatic food detection in egocentric images using artificial intelligence technology.

Public health nutrition
OBJECTIVE: To develop an artificial intelligence (AI)-based algorithm which can automatically detect food items from images acquired by an egocentric wearable camera for dietary assessment.

Training for mobility with exoskeleton robot in spinal cord injury patients: a pilot study.

European journal of physical and rehabilitation medicine
BACKGROUND: Wearable robots are people-oriented robots designed to be worn all day, thus helping in the daily activities. They can assist in walking, running, jumping higher or even lifting objects too heavy in normal conditions.

Using echo state networks for classification: A case study in Parkinson's disease diagnosis.

Artificial intelligence in medicine
Despite having notable advantages over established machine learning methods for time series analysis, reservoir computing methods, such as echo state networks (ESNs), have yet to be widely used for practical data mining applications. In this paper, w...

Predictors of activities of daily living outcomes after upper limb robot-assisted therapy in subacute stroke patients.

PloS one
BACKGROUND: Upper limb recovery is one of the main goals of post-stroke rehabilitation due to its importance for autonomy in Activities of Daily Living (ADL). Although the efficacy of upper limb Robot-assisted Therapy (RT) is well established in lite...

Activities suggestion based on emotions in AAL environments.

Artificial intelligence in medicine
The elderly population is increasing and the response of the society was to provide them with services directed to them to cope with their needs. One of the oldest solutions is the retirement home, providing housing and permanent assistance for the e...

Long-term use of the JACO robotic arm: a case series.

Disability and rehabilitation. Assistive technology
PURPOSE: Past research with JACO has principally focused on the short-term impacts on new users. Therefore, this study aims to document the long-term impacts of this assistive device on users and their family caregivers following prolonged use.

Efficacy of the Regent Suit-based rehabilitation on gait EMG patterns in hemiparetic subjects: a pilot study.

European journal of physical and rehabilitation medicine
BACKGROUND: The recovery of the functional limb mobility of patients with cerebral damages can take great benefit of the role offered by proprioceptive rehabilitation. Recently have been developed a special Regent Suit (RS) for rehabilitative applica...