Plenary Lecture
9:20-10:00 (JST)
Stephen Lord
Neuroscience Research Australia, Australia
Voluntary and reactive step training for the prevention of falls in older people
[Abstract]
Step training is defined as training of volitional or reactive steps while standing or walking in response to environmental challenges. For example, stepping onto a target, avoiding an obstacle or responding to a postural perturbation large enough to require reconfiguration of the base of support. Volitional step training uses stepping targets or distractors (no-go zones) whereas reactive step training exposes participants to repeated mechanical perturbations that induce stepping responses. There is growing evidence for step training programs to improve balance and prevent falls in older people. Accurate and appropriately timed stepping is crucial for avoiding falls as it underpins many daily tasks including obstacle and stair negotiation as well as recovery from slipping and tripping. A systematic review of seven randomised controlled trials, showed volitional and reactive step training in older people could reduce falls by 50%. The promising effects are likely due to the high task-specificity of step training to real world situations, such as trips and slips, leading to improved reactive balance and responses to avoid falling. This presentation will place step training within the context of interventions for preventing falls and synthesise the findings of recent trials that have included step training as a fall prevention strategy.
10:00-10:40 (JST)
Rezaul Begg
Victoria University, Australia
Tripping biomechanics and application of assistive technologies for falls prevention
[Short Biography]
Professor Rezaul Begg received his BSc and MSc in Electrical Engineering from Bangladesh University of Engineering and Technology (BUET) and a PhD in Biomedical Engineering from the University of Aberdeen, UK. At Victoria University he is the Chair in Assistive Technologies within the Program in Assistive Technology Innovation (PATI), and leads a multidisciplinary “Gait and Intelligent Technologies” research group. He uses a combination of engineering and biomechanical principles to understand and diagnose locomotion-related deficits, and to provide intelligent technology solutions to improving walking efficiency and safety, and minimising injuries during manual handling tasks. He has published one research monograph, 4 books and over 300 refereed papers in scientific journals and conference proceedings. Professor Begg is Associate Editor of Frontiers in Bioengineering and Biotechnology and an editorial board member of the Journal of Biomechanics and Sensors.
[Abstract]
The primary cause of falls is tripping-related balance loss due to foot-ground contact when accommodating small surface irregularities or obstacles. A fundamental requirement of human locomotion is maintaining foot elevation to avoid tripping, due to destabilising contact with the walking surface. Safety is also compromised by disorders due to ageing, neurological diseases and other causes. Biomechanically, tripping can be defined as an event in which the most distal feature of the swing limb, usually the lowest part of the shoe or foot, makes unanticipated contact with either the supporting surface or objects on it. When stability cannot be recovered, the individual sustains a fall. Minimum foot clearance (MFC) approximately mid-swing in the gait cycle poses the greatest tripping risk, because the foot passes within only 1.0-2.0 cm of the ground. This presentation will focus on two areas. First, the fundamental biomechanics of foot trajectory control, and associated tripping probability modelling of MFC distributions from data sets extending to hundreds of step cycles. The second focus will be advances in gait-assisting technologies; combining data from wearable sensors, machine learning algorithms to predict foot-obstacle contact risk and exoskeleton-assisted joint activation to provide corrective joint control.
July 23 (Sat.), 2022
9:00-9:40 (JST)
Kenichi Harano
Institute of Sport Science, ASICS Corporation, Japan
High-performance design of sports gear based on tribology
[Short Biography]
[Abstract]
Sports gear is constantly evolving to maximize user performance, from top athletes to enthusiasts working to improve their health. However, it is also important for such gear to help prevent injury and provide comfort to users. To this end, shoes are generally designed based on eight major functional properties. Factors that maximize the ability include "lightness" that reduces the burden on the body, "grip" that tightly captures the surface, and "durability" that maintains various functionalities that shoes should develop. From an injury prevention perspective, "cushioning" absorbs the reaction force when making contact with the ground, and "stability" suppresses excessive movement of the subtalar joint. To maintain comfort, factors of "fitting" and "flexibility" that follow the movement of the foot and "breathability" that keeps the temperature and humidity inside shoes comfortable are considered. In particular, research on shoe grip is important not only for performance enhancement but also for safety, such as fall prevention. In this lecture, after explaining techlonogy transition of sports gear, research cases will be discussed, including that concerning the marathon shoes in use at the 2021 Summer Olympic Games held in Tokyo as an example.
9:40-10:20 (JST)
Yasuhisa Hirata
Tohoku University, Japan
Adaptable AI-enabled robots to create a vibrant society
[Short Biography]
Yasuhisa Hirata is a Professor in the Department of Robotics at Tohoku University, Sendai, Japan. He received the B.E., M.E., and Ph.D. degrees in mechanical engineering from Tohoku University in 1998, 2000, and 2004, respectively. He has been conducting research and development on non-driving robots with high safety and wearable devices with vibration devices, aiming to develop robots that support the user to perform independent activities. He is also conducting research and development of multi-robot cooperative systems that can be applied to a wide range of fields from human assistance to environmental exploration. He is currently working on the introduction of human-assistive/human function-enhancing robots, especially in the fields of nursing care and healthcare as the project manager of the Moonshot R&D program in Japan. He is also serving as an AdCom member of IEEE Robotics and Automation Society (RAS), an associate vice-president for the Technical Activity Board of IEEE RAS, and Co-chairs of IEEE RAS Technical Committee on Rehabilitation and Assistive Robotics.
[Abstract]
This talk introduces our Moonshot project which is a project in the National Research and Development (R&D) program in Japan. The Moonshot program promotes high-risk, high-impact R&D aiming to achieve ambitious Moonshot Goals and solve issues facing future society such as super-aging populations. Our project is accepted under the Moonshot Goal 3: Realization of AI robots that autonomously learn, adapt to their environment, evolve in intelligence, and act alongside human beings, by 2050. Our project aims to create adaptable AI-enabled robots available in a variety of places. We are now developing a variety of assistive robots called the Robotic Nimbus which can change their shape and form according to the user’s condition, environment, and the purpose of the task, and provide appropriate assistance to encourage the user to take independent action. Especially, in this talk, we focus on the human-assistive/human function-enhancing robots in the fields of nursing care and healthcare including robots for preventing a fall during human daily activities.