A Mobile Robot for Following, Watching and Detecting Falls for Elderly Care

Amari, Tomoya; Satoru, Nakayama; Hoshina, Atsushi; Sugaya, Midori

doi:10.1016/j.procs.2017.08.125

Cited by 25 publications

(11 citation statements)

References 3 publications

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“…33 This technology could readily be added to existing, commercially marketed home health robots, and with further miniaturization and adaption could also be implemented in smartphones and smartwatches. 34,35 Stroke symptom detection applications Somatosensory deficits are common in acute stroke. Most sensory deficits occur as accompaniments to major motor, language, visual, and other domain impairments.…”

Section: Technologies Assessing Somatosensory Function Through Interactions With Device Surfacesmentioning

confidence: 99%

Automatic Acute Stroke Symptom Detection and Emergency Medical Systems Alerting by Mobile Health Technologies: A Review

Bat-Erdene¹,

Saver²

2021

Journal of Stroke and Cerebrovascular Diseases

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Objectives: To survey recent advances in acute stroke symptom automatic detection and Emergency Medical Systems (EMS) alerting by mobile health technologies. Materials and methods: Narrative review Results: Delayed activation of EMS for stroke symptoms by patients and witnesses deprives patients of rapid access to brain-saving therapies and occurs due to public unawareness of stroke features, cognitive and motor deficits produced by the stroke itself, and sleep onset. A promising emerging approach to overcoming the inherent biologic constraints of patient capacity to self-detect and respond to stroke symptoms is continuous monitoring by mobile health technologies with wireless sensors and artificial intelligence recognition systems. This review surveys 11 sensing technologies -accelerometers, gyroscopes, magnetometers, pressure sensors, touch screen and keyboard input detectors, artificial vision, and artificial hearing; and 10 consumer device form factors in which they are increasingly implemented: smartphones, smart speakers, smart watches and fitness bands, smart speakers/voice assistants, home health robots, smart clothing, smart beds, closed circuit television, smart rings, and desktop/laptop/tablet computers. Conclusions: The increase in computing power, wearable sensors, and mobile connectivity have ushered in an array of mobile health technologies that can transform stroke detection and EMS activation. By continuously monitoring a diverse range of biometric parameters, commercially available devices provide the technologic capability to detect cardinal language, motor, gait, and sensory signs of stroke onset. Intensified translational research to convert the promise of these technologies to validated, accurate real-world deployments are an important next priority for stroke investigation.

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Section: Technologies Assessing Somatosensory Function Through Interactions With Device Surfacesmentioning

confidence: 99%

Automatic Acute Stroke Symptom Detection and Emergency Medical Systems Alerting by Mobile Health Technologies: A Review

Bat-Erdene¹,

Saver²

2021

Journal of Stroke and Cerebrovascular Diseases

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“…A ROS is an open source software framework primarily based on UNIX platform for operating robots. Many ROS robotics types of research have been presented (Goldhoorn et al, 2018;Jafari et al, 2014;Leigh et al, 2015;Linder and Arras, 2016;Munaro and Menegatti, 2014;Ocando et al, 2017;Tomoya et al, 2017;Wunderlich et al, 2017;Xiao et al, 2017;Cousins, 2010). ROS has three levels of concepts: the file system level, the computation graph level, and the community level.…”

Section: Robot Operating System (Ros)mentioning

confidence: 99%

“…The improve in robotics capabilities have place robots in a new environment such as replacing humans in unpleasant environments, such as doing repetitive works or operating in highly radioactive zones. These are great examples of how mobile robots have started to coexist with us and assist human effectively (Tomoya et al, 2017;Wunderlich et al, 2017;Xiao et al, 2017).…”

Section: Introductionmentioning

confidence: 99%

“…The autonomous mobile robot can assist and service blind people in mobility (Gunardi and Wibowo, 2015;Cai and Matsumaru, 2014;Lee et al, 2013). Older adults who have impaired memory or cognitive problems can make use of such companion when moving around outside (Tomoya et al, 2017;Wunderlich et al, 2017;Oliver et al, 2012). There are various other useful applications of such system besides assisting the needy such as guiding for visitors, campus mobility, and item delivery.…”

Section: Introductionmentioning

confidence: 99%

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Human Following on Ros Framework a Mobile Robot

Priyandoko

Wei

Achmad

2018

Sinergi

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Service mobile robot is playing a more critical role in today's society as more people such as a disabled person or the elderly are in need of mobile robot assistance. An autonomous person following ability shows great importance to the overall role of service mobile robot in assisting human. The objective of this paper focuses on developing a robot follow a person. The robot is equipped with the necessary sensors such as a Microsoft Kinect sensor and a Hokuyo laser sensor. Four suitable tracking methods are introduced in this project which is implemented and tested on the person following algorithm. The tracking methods implemented are face detection, leg detection, color detection and person blob detection. All of the algorithms implementations in this project is performed using Robot Operating System (ROS). The result showed that the mobile robot could track and follow the target person based on the person movement.

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“…Therefore, the movement of the device was based on the prediction of the user displacement. Other works related to fall prevention and physical assistance robots for the elderly population can be observed in [14][15][16].…”

Section: Introductionmentioning

confidence: 99%

Prototype of Robotic Device for Mobility Assistance for the Elderly in Urban Environments

Leite

Figueiredo

Vellasco

2020

Sensors

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This study aims to develop a prototype of an autonomous robotic device to assist the locomotion of the elderly in urban environments. Among the achievements presented are the control techniques used for autonomous navigation and the software tools and hardware applied in the prototype. This is an extension of a previous work, in which part of the navigation algorithm was developed and validated in a simulated environment. In this extension, the real prototype is controlled by an algorithm based on fuzzy logic to obtain standalone and more-natural navigation for the user of the device. The robotic device is intended to guide an elderly person in an urban environment autonomously, although it also has a manual navigation mode. Therefore, the device should be able to navigate smoothly without sudden manoeuvres and should respect the locomotion time of the user. Furthermore, because of the proposed environment, the device should be able to navigate in an unknown and unstructured environment. The results reveal that this prototype achieves the proposed objective, demonstrating adequate behaviour for navigation in an unknown environment and fundamental safety characteristics to assist the elderly.

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A Mobile Robot for Following, Watching and Detecting Falls for Elderly Care

Cited by 25 publications

References 3 publications

Automatic Acute Stroke Symptom Detection and Emergency Medical Systems Alerting by Mobile Health Technologies: A Review

Automatic Acute Stroke Symptom Detection and Emergency Medical Systems Alerting by Mobile Health Technologies: A Review

Human Following on Ros Framework a Mobile Robot

Prototype of Robotic Device for Mobility Assistance for the Elderly in Urban Environments

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