Outline and Objectives
Preserving and encouraging mobility in the elderly and adults with chronic conditions is of paramount importance. Physical inactivity fosters the onset of cardiovascular diseases and diabetes, raises the risk of hypertension, osteoporosis, and even psychological illnesses, and leads to muscle reduction and weakening. The latter, in particular, may perilously increase the risk of falls that, along with consequent injuries, are reported as a significant public health problem all over the world. The prevention of the degenerative effects of immobilization depends on how the individuals are urged and supported to stand and walk. For this reason, a branch of research has been devoted to the development of devices and strategies to assist people in walking and balance.
For individuals who maintain some level of motor capabilities but need augmentative means to ambulate, the most common solutions are canes and walkers. The latter supports the users' weight, enhances their stability, and partly restores confidence. Nevertheless, traditional tools suffer from several drawbacks, requiring sufficient force output to move and handle the device, lack of adaptability with the human motion, and shortage of stability assurance. The next generation of walking-aid devices should comply with the users' intentions without inducing physical fatigue and suit their subject-specific needs and characteristics. In addition, to navigate complex and ever-varying environments, they should feature advanced monitoring capability, which could enhance the awareness of the users about the surroundings and how to move within them. Promising attempts of smart walkers and robotic canes have been recently proposed in this direction. However, a great scope of improvement is envisaged in terms of control strategy, human intention estimation, monitoring capabilities, and adaptation to the users.
On the other hand, for individuals with postural instability (i.e., due to vestibular deficits) who do not require mechanical support, feedback interfaces proved to be a promising approach in improving balance. Visual, auditory, electrotactile, and vibrotactile feedback interfaces provide additional sensory information and can help to increase stability, decreasing the postural sway and even the risk of falling. Plenty of literature exists on feedback strategies to enhance balance during standing; however, not many authors examined the effect of sensory stimuli while walking. Moreover, several interrogatives concerning the type of feedback, amount of stimuli, instructional cues, and task-dependent features still require a thorough response.
The improvement and advancement of the aforementioned systems are key to enabling a person with a disability to live independently and carry out everyday activities. Likewise, it is imperative to discuss the challenges that must be faced to make the use of intelligent walking and balancing-aid devices in domestic ambient and hospitals a reality.
This workshop will address the use of various robotic devices (e.g., mobile manipulators, robotic canes, smart walkers, feedback interfaces) to assist in balancing and walking elderly or individuals with diminished ambulation capabilities. In particular, the workshop will specifically focus on the emerging trends and perspectives on this topic, attempting to answer the following questions:
- What are the main issues and limitations of the traditional devices, and how can they be overcome through robotic devices?
- What should be the main features and requirements of such robotic devices?
- What are the challenges to introducing them into users' daily lives and the resulting benefits?
To advance research on those questions, the workshop aims to bring together researchers who introduced and investigated different strategies and devices to assist the users both in balancing and walking. By providing a platform for top researchers to share their work, we aim to generate a fruitful discussion and inspire new perspectives toward the extension and application of robotic assistive devices.
Untitled Basic Web Content
The workshop will take place on Thursday 27th of October, 2022. Japan Standard Time (JST).
|09.00 – 09.30||Introduction by the organizers|
|09.30 – 10.00||Assistive Robotics for Supporting Frail Older Adults in Daily Activities, Rehabilitation Exercise, and Fall Risk Mitigation by Harry Asada|
|10.00 – 10.30||Wheeled Mobile Manipulators and Exoskeletons for Intelligent Mobility Assistance by Mahdi Tavakoli|
|10.30 – 11.00||Advanced human-robot interaction strategies for walker-assisted gait by Anselmo Frizera Neto|
|11.00 – 11.30||Coffee Break|
|11.30 – 12.00||Smart Wearable System with Real-Time Feedback to Improve Human Balance and Walking Ability by Cristina Zong-Hao Ma|
|12.00 – 13.00||Lunch Break|
|13.00 – 14.00||Extended Abstract Presentations|
|14.00 – 14.30||Human-Robot Interaction and Control Algorithms of Intelligent Walking-Aid Robots by Jian Huang|
|14.30 – 15.00||Walk-IT: a modular reconfigurable rollator for nonintrusive gait analysis by Cristina Urdiales|
|15.00 – 15.30||Coffee Break|
|15.30 – 16.00||Bio-inspiration in gait assistance: achieving adaptive behaviours by Virginia Ruiz Garate|
|16.00 – 16.30||Developing Biomedical devices by Cristina Santos|
Electrical Engineering Department, Federal University of Espirito Santo (Brazil)
Advanced human-robot interaction strategies for walker-assisted gait [video]
This talk presents different interaction strategies applied to the control of different smart walkers developed in the past 12 years at the Center for Assistive Technology (Federal University of Espirito Santo). Starting with the UFES Smart Walker, several kinematic and dynamic parameters were extracted from the cognitive and physical human-robot interaction and were used to control the robotic device in a robust and natural manner. After that, the robotic device was inserted in complex environments and information from the surroundings were inserted into the control loop, creating different advanced human-robot interaction strategies. Haptics and proxemics concepts were inserted into the rehabilitation device allowing the robot to be controlled as the user was able to better perceive the environment. As the complexity of the robotic devices increased, new cloud robotic solutions emerged giving birth to the UFES CloudWalker, a smart walker framework designed to be simple and efficient while delegating complex tasks to the cloud. Currently, we seek to create advanced rehabilitation strategies through the combination of virtual reality systems and the smart walkers to allow the realization of advanced rehabilitation strategies. The UFES vWalker is being designed to offer the advantage of inserting patients into simulation environments with virtual obstacles, and therefore, care centers do not depend on specific equipment and physical space for quality care.
Industrial Electronics Department, University of Minho, Portugal.
Developing Biomedical devices [video]
More advanced and reliable robotic technologies for the healthcare industry are required since many industrialized countries are suffering from limited resources for healthcare, and an ever-increasing number of disabled and elderly population. Existing assistive technologies are unsatisfactory in meeting personal needs and fulfilling the required functions at a reasonable cost while being used in hospitals, schools, and homes in therapeutic programs that monitor, encourage, and assist their users. Any innovation to improve the capability of personalization or reduce the ratio of price and performance will promote the applications of robotic technologies in healthcare significantly, addressing more functionalities and targeted patients. This presentation summarizes developments of assistive technologies for the disabled population to identify research targets that have guided the author research towards tangible, and measurable progress. Thus, it discusses the demands for assistive technologies for the disabled population, identifying the advantages and disadvantages of rehabilitation robots as assistive technologies and the issues involved in their development. Further, it selects a few critical challenge tasks in developing advanced rehabilitation robots to demonstrate progress. Further, presents some case studies of the author.
Department of Electronic Technology, University of Malaga, Spain
Walk-IT: a modular reconfigurable rollator for nonintrusive gait analysis [video]
Most gait analysis studies on people with disabilities are often constrained to controlled environments and/or limited time periods. This usually happens because tests involve expensive/complex equipment and/or require wearable sensors that may not be accepted by users for long periods of time. In order to provide continuous, long term monitorization, sensors should be cheap, easy to configure and non-intrusive and also not constrained to a specific environment. An obvious solution is to attach sensors to assistive devices like rollators or wheelchairs. However, robotized commercial devices are usually costly and require a yearly maintenance fee. On the other hand, experimental devices might be difficult to duplicate and to be accepted by Ethical Committees for testing in clinical facilities. Walk-IT offers a solution to these problems. It consists of a set of open licensed modules -shared on GitHub- that can be easily attached to commercial non-robotized rollators on a need basis. Depending on the number of attached modules and sensors, rollators may monitorize gait with different degrees of precision and even passively assist users. Thus, Walk-IT can be adapted to different budgets and experiment constraints. In its simplest version, Walk-IT monitorizes gait relying uniquely on wheel odometry and weight differences on the rollator handlebars. Precision may be increased by adding other modules, e.g. a sensor to track users' feet. This talk introduces Walk-IT, plus two modular configurations for gait analysis. All software has been developed under ROS.
Department of Rehabilitation Sciences, Hong Kong Polytechnic University, China.
Smart Wearable System with Real-Time Feedback to Improve Human Balance and Walking Ability [video]
Balance and gait disorder has been the second leading cause of falls in older people and patients. To improve the balance and gait performance, we have developed a series of smart wearable systems that can detect the balance and gait performance of users, and then provide the corresponding feedback/reminder to users in real-time since 2013. We have evaluated the effects of such system on balance and gait performance in healthy young and older adults, and patients with stroke. The positive results supported that such system can effectively improve the static standing postural balance, standing balance under perturbation, and gait pattern. Our latest research also supported that such system could facilitate the lower-limb sensorimotor function of stroke survivors. Such system could not only improve the balance and gait performance of older people and patients who are prone to falls, but also assist the rehabilitation professionals’ clinical practice of balance and gait trainings for patients.
Department of Mechanical Engineering, Massachusetts Institute Of Technology, USA
Assistive Robotics for Supporting Frail Older Adults in Daily Activities, Rehabilitation Exercise, and Fall Risk Mitigation [video]
This workshop talk will present three on-going research projects on assistive robotics for supporting frail older adults by focusing on mobility and balancing.
a). “Handle Anywhere”: a mobile robot arm for providing bodily support to frail older adults. Traditionally, grab bars are installed in bathrooms and other places in a house to assist a frail older adult at specific locations of high risk. These grab bars, however, are placed only on existing walls and other fixtures, which are not necessarily optimal locations for supporting a frail older adult. Here, we will present a flexible robotic handle that can be placed anywhere – Handle Anywhere – within a house. A mobile robot can move to the frail older adult as needed and can position its arm handle at an optimal location, so that the older adult can grab it for walking, sit-to-stand transitions, and other daily activities needing physical assistance.
b). Robot-assisted rehabilitation exercise for frail older adults. “Tai Chi” - a traditional Asian mind-body movement exercise - is highly effective in improving balance and reducing fall risk in ambulatory older adults. Although the Tai Chi exercise is effective particularly for frail older adults to maintain their balancing function, safety is a major concern. Here, we present a buddy robot that supports the body of a frail older adult during the exercise. The robot holds a pair of cables connected to a garment of the older adult so that the body can be suspended in case the older adult is losing balance. The robot can move in response to the movement of an older adult, so that he/she can move freely and safely during the exercise.
c). A fall prediction and prevention system. Finally, a real-time fall prediction system using an IMU-based body motion sensor and machine learning will be presented. A new algorithm for detecting an early trait of losing balance is developed, so that the body can be suspended with the cables to prevent a hard hit on a floor from occurring. A non-intrusive cable suspension system that connects the garment of an older adult and a walker-type fall prevention structure is presented. The walker can change its footprint (BOS) based on the fall prediction signal in real-time, so that the walker does not tip but support the body of the older adult.
Finally, the potentials of these assistive robots and their socioeconomic impact will be addressed.
Engineering, Design and Mathematics Department, University of the West of England, United Kingdom
Bio-inspiration in gait assistance: achieving adaptive behaviours [video]
Physically assistive technologies are a growing topic of interest nowadays due to the increasing amount of population in need of physical support and the decreasing available healthcare force. Though great advancements are seen in research regarding physically assistive technologies for balancing and walking, these are rarely found in real-world contexts. Apart from the many technological challenges associated with their developments, other social and organization challenges are behind this lack of adoption. End-users, even if presented with these technologies, tend to refuse, or give them up quite rapidly. A challenge that lies at the intersection between the technical and social issues, is that of user adaptability. Gait is a very characteristic feature of individuals, up to the point when we can distinguish someone by the way they walk. However, currently used assistive devices are mostly controlled following pre-recorded or fixed gait patterns with few variables that can be adjusted. Though this can provide some adaptation, produced trajectories still differ significantly from the individual gait pattern of the person. The discrepancy between the provided assistance and the users could lead to injuries in long-term use, and usually renders discomfort which prompts the early abandonment of these devices. This presentation will mainly focus on presenting two different works that aim to address this problem: a bio-inspired control for exoskeletons which provides continuous adaptive assistance during ambulation; and a study on human movement and balance during sit-to-stand, which can predict individual trajectories to be used by assistive robotic devices.
is a postdoctoral researcher at the Human-Robot Interfaces and Physical Interaction lab at Istituto Italiano di Tecnologia (IIT). She received the B.S., M.S., and Ph.D. in Department of Electronics, Information and Bioengineering from Politecnico di Milano, Milano, Italy in 2014, 2016, and 2020, respectively. She is currently involved in Horizon-2020 project SOPHIA and ERC project Ergo-Lean. % and also active in a technology transfer initiative with several industrial partners, the JOiiNT lab at Kilometro Rosso Innovation District. She was the winner of the Solution Award 2019 (Premio Innovazione Robotica at MECSPE2019), the KUKA Innovation Award 2018 and IEEE Italy Section 2021 PhD Thesis Award by ABB - New Challenges for Energy and Industry. Her research interests include human kinodynamic states real-time monitoring, human ergonomics estimation and assessment, physical human-robot interaction and feedback interfaces.
is a postdoctoral researcher at the Human-Robot Interfaces and Physical Interaction at Istituto Italiano di Tecnologia (IIT). He received the B.S., M.S., and the PhD in Mechatronics from the University of Malaga in 2015, 2017, and 2020, respectively. He is currently involved in the Horizon-2020 project SOPHIA and ERC project Ergo-Lean. He has contributed to several Spanish and European projects related to search-and-rescue, physical robotic assistance, and Human-Robot Collaboration in Industrial environments. He has been served as a reviewer for high-impact journals and conferences such as IEEE RAM, RA-L, ICRA, IROS, ToH, etc. His research interests include HRC, human modeling, and haptic perception.
Mahdi Tavakoli is a Professor in the Department of Electrical and Computer Engineering, University of Alberta, Canada. He received his BSc and MSc degrees in Electrical Engineering from Ferdowsi University and K.N. Toosi University, Iran, in 1996 and 1999, respectively. He received his PhD degree in Electrical and Computer Engineering from the University of Western Ontario, Canada, in 2005. In 2006, he was a post-doctoral researcher at Canadian Surgical Technologies and Advanced Robotics (CSTAR), Canada. In 2007-2008, he was an NSERC Post-Doctoral Fellow at Harvard University, USA. Dr. Tavakoli’s research interests broadly involve the areas of robotics and systems control. Specifically, his research focuses on haptics and teleoperation control, medical robotics, and image-guided surgery. Dr. Tavakoli is the lead author of Haptics for Teleoperated Surgical Robotic Systems (World Scientific, 2008). He is a Senior Member of IEEE and an Associate Editor for IEEE Robotics and Automation Letters, Journal of Medical Robotics Research, IET Control Theory & Applications, and Mechatronics.
Wheeled Mobile Manipulators and Exoskeletons for Intelligent Mobility Assistance [video]
Neurological impairments, e.g., spinal cord injury (SCI), stroke, multiple sclerosis (MS), and cerebral palsy (CP), are limiting independent life for millions of people all over the world. Recent advancements in the development of lower-limb exoskeletons have created an excellent environment to provide more efficient rehabilitation/assistance for people with mobility impairments. However, improvements must be made in both hardware and software design for exoskeletons before their widespread use. In this research, we are focused on providing personalized and safe locomotion patterns as one of the significant shortcomings of most available exoskeletons. In order to generate user-specific walking trajectories, a new adaptable gait trajectory shaping method is proposed by defining central pattern generators (CPGs). To increase the level of safety, an integrated control strategy is developed for both locomotion trajectory planning and postural stability, enabling shared autonomy between the human and lower-limb exoskeleton. Finally, reinforcement learning is integrated with the adaptive CPG dynamics to facilitate personalization of therapy.
Jian Huang graduated from Huazhong University of Science and Technology (HUST), China in 1997 and received the Master of Engineering degree from HUST in 2000. He received his Ph.D from HUST in 2005. From 2006 to 2008, he was a postdoctoral researcher in the Department of Micro-Nano System Engineering and Department of Mechano-Informatics and Systems, Nagoya University, Japan. In 2015, he is also awarded a JSPS Invitation Fellowship working in Nagoya University. He is currently a full professor with the School of Artificial Intelligence and Automation, HUST. He is also a guest professor in Nagoya University of Japan and University Paris-Est Créteil (UPEC) of France. His main research interests include rehabilitation robot, robotic assembly, networked control systems and bioinformatics. He is an IEEE Senior Member and has published more than 300 research papers (including more than 90 SCI-indexed journal papers) in some academic journals and conferences. He is currently an Associate Editor of IEEE Transactions on Fuzzy Systems, Frontiers in Neurorobotics, an editor of ROBOMECH Journal – Springer, and the academic editor of PLOS One
Human-Robot Interaction and Control Algorithms of Intelligent Walking-Aid Robots [video]
Lower extremity muscle deficits caused by aging, neurological diseases, and sports injuries significantly limits patients' ability to engage in daily living activities. Moreover, the growing elderly population causes the shortage of young people for nursing care. Therefore, intelligent walking-aid robots find their application in the nursing and walking-aid field for these people with lower extremity muscle deficits. Although walking-aid robots have been extensively studied, there are still many challenges in practical applications. In the walking assistance, it is difficult for the robot to accurately extract and quantitatively describe the human motion intention, and it is difficult to accurately recognize diverse walking states. In the human-following and supervision, it is difficult for the robot to obtain human sagittal information in real time, and it is difficult to realize the non-contact human-following within the fixed human-robot relative posture. In the gait analysis, it is still difficult to accurately extract gait parameters based on main-stream research of onboard sensors. In order to solve these challenges, in this study, considering the need for walking-aid, independent walking, and providing the gait analysis and evaluation results for physicians during the rehabilitation of patients with varying lower limb muscles strength, the intelligent walking-aid robots have been developed, which realizes the intention-based admittance control algorithm during the walking-aid mode, the data-driven based human-robot coordination walking state monitoring, the human-following control with fixed relative posture as well as the gait spatial-temporal parameter extraction algorithm and walking ability evaluation algorithm based on the onboard laser range finders