Background: Recent advancements in and the proliferation of autonomous mobility technology, such as intelligent wheelchairs, have made it possible to provide mobility services for patients with reduced mobility due to musculoskeletal disorders. In the present study, we conducted a preliminary clinical study to assess the safety and feasibility of in-hospital autonomous transportation using a driverless mobility (wheelchair) for patients with musculoskeletal disorders.
Methods: From January to February 2022, 51 patients with musculoskeletal disorders exhibiting gait disturbance who presented to our institution were included in the present study. Driverless mobility rides were conducted over a straight-line distance of 100 m from the orthopaedic outpatient reception to the payment counter after the outpatient consultation. We assessed the quality of life using an EQ-5D-5 L index and pain using a VAS score before riding the mobility to investigate the patient's condition. After the ride, a questionnaire survey was conducted to assess patient satisfaction on a 5-point scale. In addition, adverse events during the mobility ride were investigated.
Results: Overall satisfaction levels showed that 44 out of 51 (86%) patients rated the level as 3 or higher. There were no significant differences in the level of satisfaction based on the cause of disorders or EQ-5D-5 L Index. Among 19 patients who rated the level of satisfaction as 2-3, the ratio of postoperative patients and those with pain tended to be higher (p < 0.05). While 26 of 51 (51%) patients reported moments of feeling unsafe during the mobility ride, no actual adverse events, such as collisions, were observed.
Conclusions: An in-hospital autonomous transportation service using a driverless mobility for patients with musculoskeletal disorders demonstrated high satisfaction levels and was safe with no severe adverse events observed. The expansion of autonomous mobility deployment is expected to achieve mobility as a service in medical care.
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http://dx.doi.org/10.1186/s12891-024-07417-x | DOI Listing |
Sensors (Basel)
July 2024
School of Engineering, University of Central Lancashire, Preston PR1 2HE, UK.
This paper aims to improve the steering performance of the Ackermann personal mobility scooter based on a new meta-heuristic optimization algorithm named Differential Harris Hawks Optimization (DHHO) and the modeling of the steering encoder. The steering response in the Ackermann mechanism is crucial for automated driving systems (ADS), especially in localization and path-planning phases. Various methods presented in the literature are used to control the steering, and meta-heuristic optimization algorithms have achieved prominent results.
View Article and Find Full Text PDFBMC Musculoskelet Disord
May 2024
Department of Orthopaedic Surgery, Institute of Medicine, University of Tsukuba, 1-1-1, Tennodai, Tsukuba City, Ibaraki, 305-8575, Japan.
Background: Recent advancements in and the proliferation of autonomous mobility technology, such as intelligent wheelchairs, have made it possible to provide mobility services for patients with reduced mobility due to musculoskeletal disorders. In the present study, we conducted a preliminary clinical study to assess the safety and feasibility of in-hospital autonomous transportation using a driverless mobility (wheelchair) for patients with musculoskeletal disorders.
Methods: From January to February 2022, 51 patients with musculoskeletal disorders exhibiting gait disturbance who presented to our institution were included in the present study.
Sensors (Basel)
August 2023
School of Engineering, RMIT University, Melbourne, VIC 3000, Australia.
With the increasing use of automated vehicles (AVs) in the coming decades, government authorities and private companies must leverage their potential disruption to benefit society. Few studies have considered the impact of AVs towards mode shift by considering a range of factors at the city level, especially in Australia. To address this knowledge gap, we developed a system dynamic (SD)-based model to explore the mode shift between conventional vehicles (CVs), AVs, and public transport (PT) by systematically considering a range of factors, such as road network, vehicle cost, public transport supply, and congestion level.
View Article and Find Full Text PDFPLoS One
May 2023
Université Paris-Saclay, UVSQ, CESP, Team MOODS, Le Kremlin-Bicêtre, France.
Background: Assessing successful ageing (SA) is essential to identify modifiable factors in order to enforce health promotion and prevention actions. SA comprises 3 dimensions: an active engagement with life, a low probability of disease and disease-related disability, and a high cognitive and physical functional capacity. Driving seems to be linked to SA as it is a mean to preserve social interactions and requires preserved functional and cognitive status.
View Article and Find Full Text PDFSci Rep
December 2022
Radiolabs, Corso d'Italia 19, 00198, Rome, Italy.
The development and manufacture of self-driving cars (SDCs) have triggered unprecedented challenges among car manufacturers and smart road operators to accelerate awareness and implementation of innovative technologies for cooperative, connected and automated mobility (CCAM), especially those with a high level of automation and safety. Safety improvement is a pre-requisite to justify and unleashing a mass deployment of connected and driverless cars to reach the goal of zero-accident in 2050 set by the European Commission. Behind these motivations a well-justified and widely acceptable high-level safety target for SDCs is mandatory.
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!