Bath-Ambience-A mechatronic system for assisting the caregivers of bedridden people

The health of older people is receiving special attention and dedication nowadays, with the aim of increasing their general wellbeing and quality of life. Studies into different aspects of the care of the elderly have found that emphasis should be given to solving problems related to bathing in different situations and environments. In particular, it is important to develop new assistive technologies to streamline and ease the burden of a caregiver's daily tasks. Generally-speaking, in the case of bedridden patients, bathing is typically carried out manually by a caregiver, using towels, sponges, and a water basin. Nevertheless, this apparently simple task needs some precautions in order to avoid the risk of microbial infections, falls and other injuries. With that in mind, this paper presents the design of a portable washing system, called Bath-Ambience, which enables bedridden patients to be bathed efficiently without having to be moved from their position. This portable system can be installed in different situations, both in a domestic setting, and in specialized institutions, and allows the caregiver to perform the bathing tasks without compromising health and safety, thereby making it possible to offer a comfortable and hygienic procedure to patients, improving their quality of life. This paper presents the design of the portable Bath-Ambience washing system, which provides efficient assistance for bathing bedridden patients without moving them to another place. This system is mainly dedicated for integration a smart home application in to allow bathing everywhere.info:eu-repo/semantics/publishedVersio

Multidimensional Capacitive Sensing for Robot-Assisted Dressing and Bathing

Robotic assistance presents an opportunity to benefit the lives of many people with physical disabilities, yet accurately sensing the human body and tracking human motion remain difficult for robots. We present a multidimensional capacitive sensing technique that estimates the local pose of a human limb in real time. A key benefit of this sensing method is that it can sense the limb through opaque materials, including fabrics and wet cloth. Our method uses a multielectrode capacitive sensor mounted to a robot's end effector. A neural network model estimates the position of the closest point on a person's limb and the orientation of the limb's central axis relative to the sensor's frame of reference. These pose estimates enable the robot to move its end effector with respect to the limb using feedback control. We demonstrate that a PR2 robot can use this approach with a custom six electrode capacitive sensor to assist with two activities of daily living-dressing and bathing. The robot pulled the sleeve of a hospital gown onto able-bodied participants' right arms, while tracking human motion. When assisting with bathing, the robot moved a soft wet washcloth to follow the contours of able-bodied participants' limbs, cleaning their surfaces. Overall, we found that multidimensional capacitive sensing presents a promising approach for robots to sense and track the human body during assistive tasks that require physical human-robot interaction.Comment: 8 pages, 16 figures, International Conference on Rehabilitation Robotics 201