ActiDote –activity as an antidote– is a system for manual wheelchair users that takes advantage of wireless sensors to recognize activities of various intensity levels in order to allow self-tracking of the physical activity. In this paper, we describe both the hardware setup and the software pipeline that enable our system to operate. Laboratory tests using multi-modal fusion and machine learning reveal promising results on classifying activity levels and assessing energy expenditure during wheelchair propulsion on ramps of different slopes and speeds. Our results indicate that it is possible to implement a system that uses the accelerometer of a smartphone as the only sensor in the wheelchair, i.e., by attaching it to the wheelchair frame...
In an effort to make activity monitors usable by manual wheelchair users with Spinal Cord Injury (SC...
ABSTRACT: Wheelchairs are used by the people who cannot walk due to physiological or physical illnes...
The main objective is to use Machine Learning algorithms to build-up models of energy expenditure of...
ActiDote –activity as an antidote– is a system for manual wheelchair users that takes advantage of w...
ActiDote —activity as an antidote— is a system for manual wheelchair users that uses wireless sensor...
Regular participation in physical activity (PA) is vital to good health. Despite numerous reported p...
To measure physical activity in a wheelchair user is important. Disabled people have been found to b...
People with disabilities who rely on manual wheelchairs as their primary means of mobility face dail...
Due to lower limb paralysis, individuals with spinal cord injury (SCI) rely on their upper limbs for...
Physical activity in wheelchair-bound individuals can be assessed by monitoring their mobility as th...
In a system for determining in-seat behavior of a user, a sensor mat is placed on a location of the ...
Monitoring activities of daily living (ADLs) for wheelchair users, particularly spinal cord injury i...
Manual wheelchair users (MWUs) with spinal cord injury (SCI) have significantly lower levels of phys...
This study is motivated by the fact that there are currently no widely used applications available t...
Manual wheelchair users (MWUs) with spinal cord injury (SCI) are at the lower end of the physical ac...
In an effort to make activity monitors usable by manual wheelchair users with Spinal Cord Injury (SC...
ABSTRACT: Wheelchairs are used by the people who cannot walk due to physiological or physical illnes...
The main objective is to use Machine Learning algorithms to build-up models of energy expenditure of...
ActiDote –activity as an antidote– is a system for manual wheelchair users that takes advantage of w...
ActiDote —activity as an antidote— is a system for manual wheelchair users that uses wireless sensor...
Regular participation in physical activity (PA) is vital to good health. Despite numerous reported p...
To measure physical activity in a wheelchair user is important. Disabled people have been found to b...
People with disabilities who rely on manual wheelchairs as their primary means of mobility face dail...
Due to lower limb paralysis, individuals with spinal cord injury (SCI) rely on their upper limbs for...
Physical activity in wheelchair-bound individuals can be assessed by monitoring their mobility as th...
In a system for determining in-seat behavior of a user, a sensor mat is placed on a location of the ...
Monitoring activities of daily living (ADLs) for wheelchair users, particularly spinal cord injury i...
Manual wheelchair users (MWUs) with spinal cord injury (SCI) have significantly lower levels of phys...
This study is motivated by the fact that there are currently no widely used applications available t...
Manual wheelchair users (MWUs) with spinal cord injury (SCI) are at the lower end of the physical ac...
In an effort to make activity monitors usable by manual wheelchair users with Spinal Cord Injury (SC...
ABSTRACT: Wheelchairs are used by the people who cannot walk due to physiological or physical illnes...
The main objective is to use Machine Learning algorithms to build-up models of energy expenditure of...