Special Issue on Assistive and Rehabilitation Robotics

Mohammed, Samer; Park, Hae Won; Park, Chung Hyuk; Argall, Brenna

doi:10.1007/s10514-017-9627-z

Cited by 11 publications

(6 citation statements)

References 14 publications

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“…Multi-agent intelligent healthcare systems that can enable robots to select the most useful plan for unmanaged situations and communicate the choice to the physician for approval have been proposed in [45] . Home robots that support elderly people and help in coping with the problems of aging, such as disorders affecting memory, motor functions, and muscle weakness, can overcome the shortage of caregivers and healthcare providers [14] , [45] , [53] . Robotic-assisted minimally invasive surgeries such as heart surgery [46] , neurosurgery [44] , liver surgery [42] , and ultrasound [28] and MRI-guided [39] robotic interventions are more established now.…”

Section: Smart and Connected Health: Review Classification And Comparisonmentioning

confidence: 99%

Trends, Technologies, and Key Challenges in Smart and Connected Healthcare

et al. 2021

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Cardio Vascular Diseases (CVD) is the leading cause of death globally and is increasing at an alarming rate, according to the American Heart Association's Heart Attack and Stroke Statistics-2021. This increase has been further exacerbated because of the current coronavirus (COVID-19) pandemic, thereby increasing the pressure on existing healthcare resources. Smart and Connected Health (SCH) is a viable solution for the prevalent healthcare challenges. It can reshape the course of healthcare to be more strategic, preventive, and custom-designed, making it more effective with value-added services. This research endeavors to classify state-of-the-art SCH technologies via a thorough literature review and analysis to comprehensively define SCH features and identify the enabling technology-related challenges in SCH adoption. We also propose an architectural model that captures the technological aspect of the SCH solution, its environment, and its primary involved stakeholders. It serves as a reference model for SCH acceptance and implementation. We reflected the COVID-19 case study illustrating how some countries have tackled the pandemic differently in terms of leveraging the power of different SCH technologies, such as big data, cloud computing, Internet of Things, artificial intelligence, robotics, blockchain, and mobile applications. In combating the pandemic, SCH has been used efficiently at different stages such as disease diagnosis, virus detection, individual monitoring, tracking, controlling, and resource allocation. Furthermore, this review highlights the challenges to SCH acceptance, as well as the potential research directions for better patient-centric healthcare.

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Section: Smart and Connected Health: Review Classification And Comparisonmentioning

confidence: 99%

Trends, Technologies, and Key Challenges in Smart and Connected Healthcare

et al. 2021

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“…Some work has focused on methods for general-purpose mobile manipulators to assist with specific assistive tasks [24, 25]. A few tasks that have been investigated are household cleaning [26], generic in-home mobile manipulation [27, 28], shaving [29], feeding [30], picking-and-placing tasks [31], and transfers [32].…”

Section: Related Workmentioning

confidence: 99%

A system for bedside assistance that integrates a robotic bed and a mobile manipulator

et al. 2019

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Various situations, such as injuries or long-term disabilities, can result in people receiving physical assistance while in bed. We present a robotic system for bedside assistance that consists of a robotic bed and a mobile manipulator (i.e., a wheeled robot with arms) that work together to provide better assistance. Many assistive tasks depend on moving with respect to the person’s body, and the complementary physical and perceptual capabilities of the two robots help with respect to this general goal. The system provides autonomy for common tasks, as well as an interface for direct teleoperation of the two robots. Autonomy handles coarse motions of the robots by estimating the person’s pose using a pressure sensing mat and then moving the robots to configurations optimized for the task. After completing these motions, the user is given fine control of the robots to complete the task. In an evaluation using a medical mannequin, we found that the robotic bed’s motion and perception each improved the assistive robotic system’s performance. The system achieved 100% success over 9 trials involving 3 tasks. Using the system with the bed movement or the body pose estimation capabilities turned off resulted in success in only 33% or 78% of the trials, respectively. We also evaluated our system with Henry Evans, a person with severe quadriplegia, in his home. In a formal test, Henry successfully used the bedside-assistance system to perform 3 different tasks, 5 times each, without any failures. Henry’s feedback on the system was positive regarding usefulness and ease of use, and he noted benefits of using our system over fully manual teleoperation. Overall, our results suggest that a robotic bed and a mobile manipulator can work collaboratively to provide effective personal assistance and that the combination of the two robots is beneficial.

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“…First, it broadens the choices available on how users with DASH can interact with the environment. Besides using assistive devices such as exoskeleton, robotic arms or a prosthetic arm [2], people with DASH can also utilize existing computer technology which only requires a computer, a web camera and the appropriate head gesture recognition software. This could be considered as a cheaper solution.…”

Section: Implications On the Advantages Of Using Head Gesturementioning

confidence: 99%

“…The related studies supporting DASH have focused on the automation of objects for their mobility [1]. These include replacement technologies such as an exoskeleton, robotic arms or a prosthetic arm are among the common solutions for assisting people with DASH [2]. An alternatives approach to this problem is through brain computer interfacing [3], i.e.…”

Section: Introductionmentioning

confidence: 99%

Gesture Interfacing for People With Disability of the Arm, Shoulder and Hand (Dash) for Smart Door Control: Goms Analysis

Azmi

Yusof

Chiew

et al. 2019

MJCS

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People with disabilities may interact with their environment differently from other human beings. This is also the case with people with the disability of the arm, shoulder and hand (DASH). However, most environments do not include supportive design for DASH. This study aimed to explore and analyze the body parts used by people with DASH to open doors in a real-world environment and to find an efficient interface design for people with DASH to open doors through a computer interface. This study was conducted in three parts: interviews of three people with DASH, observation of the videos of people with DASH opening doors, and GOMS analysis of five designed interfaces for people with DASH to open doors/windows through a computer interface. It was found that head gesture was suitable to be used as an interaction medium and through the GOMS analysis that the Type 5 (every task has a different head gesture movement) and Type 3 (positioning heads at different vertical or horizontal positions) are two most efficient designed interfaces for head gesture with regards to opening a door.

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Special Issue on Assistive and Rehabilitation Robotics

Cited by 11 publications

References 14 publications

Trends, Technologies, and Key Challenges in Smart and Connected Healthcare

Trends, Technologies, and Key Challenges in Smart and Connected Healthcare

A system for bedside assistance that integrates a robotic bed and a mobile manipulator

Gesture Interfacing for People With Disability of the Arm, Shoulder and Hand (Dash) for Smart Door Control: Goms Analysis

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