AIMC Topic: Activities of Daily Living

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A Control Scheme to Minimize Muscle Energy for Power Assistant Robotic Systems Under Unknown External Perturbation.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
This paper proposes a novel control method to minimize muscle energy for power-assistant robotic systems that support the intended motions of a user under unknown external perturbations, using surface electromyogram (sEMG) signals. Conventional contr...

Validation of accuracy of SVM-based fall detection system using real-world fall and non-fall datasets.

PloS one
Falls are a major cause of injuries and deaths in older adults. Even when no injury occurs, about half of all older adults who fall are unable to get up without assistance. The extended period of lying on the floor often leads to medical complication...

Robot-Assisted Training for People With Spinal Cord Injury: A Meta-Analysis.

Archives of physical medicine and rehabilitation
OBJECTIVE: To investigate the effects of robot-assisted training on the recovery of people with spinal cord injury (SCI).

Development and Implementation of an End-Effector Upper Limb Rehabilitation Robot for Hemiplegic Patients with Line and Circle Tracking Training.

Journal of healthcare engineering
Numerous robots have been widely used to deliver rehabilitative training for hemiplegic patients to improve their functional ability. Because of the complexity and diversity of upper limb motion, customization of training patterns is one key factor d...

Extracting aerobic system dynamics during unsupervised activities of daily living using wearable sensor machine learning models.

Journal of applied physiology (Bethesda, Md. : 1985)
Physical activity levels are related through algorithms to the energetic demand, with no information regarding the integrity of the multiple physiological systems involved in the energetic supply. Longitudinal analysis of the oxygen uptake (V̇o) by w...

Activity Recognition for Persons With Stroke Using Mobile Phone Technology: Toward Improved Performance in a Home Setting.

Journal of medical Internet research
BACKGROUND: Smartphones contain sensors that measure movement-related data, making them promising tools for monitoring physical activity after a stroke. Activity recognition (AR) systems are typically trained on movement data from healthy individuals...

A human-oriented framework for developing assistive service robots.

Disability and rehabilitation. Assistive technology
PURPOSE: Multipurpose robots that can perform a range of useful tasks have the potential to increase the quality of life for many people living with disabilities. Owing to factors such as high system complexity, as-yet unresolved research questions a...

Unsupervised Machine Learning for Developing Personalised Behaviour Models Using Activity Data.

Sensors (Basel, Switzerland)
The goal of this study is to address two major issues that undermine the large scale deployment of smart home sensing solutions in people's homes. These include the costs associated with having to install and maintain a large number of sensors, and t...

Quantification of task-dependent cortical activation evoked by robotic continuous wrist joint manipulation in chronic hemiparetic stroke.

Journal of neuroengineering and rehabilitation
BACKGROUND: Cortical damage after stroke can drastically impair sensory and motor function of the upper limb, affecting the execution of activities of daily living and quality of life. Motor impairment after stroke has been thoroughly studied, howeve...

Robotic gait training in multiple sclerosis rehabilitation: Can virtual reality make the difference? Findings from a randomized controlled trial.

Journal of the neurological sciences
Gait, coordination, and balance may be severely compromised in patients with multiple sclerosis (MS), with considerable consequences on the patient's daily living activities, psychological status and quality of life. For this reason, MS patients may ...