Skip to main content

Special collection in association with the 2023 International Conference on aging, innovation and rehabilitation

We are happy to introduce this collection of research articles in association with the International Conference on aging, innovation and rehabilitation (ICAIR). The 2023 conference was an interdisciplinary event that brought together leading researchers, scientists, and entrepreneurs, dedicated to enhancing the quality of life for individuals who face challenges related to aging and disability (Fig. 1). The conference was jointly hosted by The KITE Research Institute | Toronto Rehabilitation Institute–University Health Network (Fig. 2) and the Rehabilitation Sciences Institute at the University of Toronto, with contributions and participation from other clinical and research institutions and hospitals worldwide.

Fig. 1
figure 1

Snapshots from the first International Conference on Aging, Innovation and Rehabilitation (ICAIR), May 2023, Toronto, Ontario, Canada

Fig. 2
figure 2

Toronto Rehabilitation Institute is Canada’s largest academic hospital dedicated to adult rehabilitation and complex continuing care and a member of the University Health Network, a network of research hospitals affiliated with the University of Toronto. KITE Research Institute is the research arm of the Toronto Rehabilitation Institute–University Health Network. KITE is a world leader in complex rehabilitation science and is dedicated to improving the lives of people living with the effects of disability, illness and aging. KITE’s areas of focus include prevention, restoration, enhanced participation, and independent living. KITE research facilities include the DriverLab, ClimateLab, CareLab, Rehab Engineering Lab, StreetLab, etc

Abstracts submitted to the conference underwent peer review process and were selected for poster or podium presentations. A small subset of the abstracts, which received the highest review scores, were invited to submit a full-length manuscript for review and potential publication in this collection. These submissions underwent standard peer-review process at the journal and, after reviews, rebuttals, and revisions, twelve were accepted for publication, representing a wide range of techniques and applications related to health monitoring, assessment, and rehabilitation.

While covering diverse topics, articles in this collection are linked through multiple connecting themes, such as functional electrical stimulation [1, 2] or the application of signal processing and artificial intelligence in solving aging and rehabilitation problems [2,3,4,5,6,7,8]. Specifically, a number of the papers in this collection [4,5,6,7] explore the application of computer vision techniques in various healthcare domains, particularly focusing on rehabilitation and mobility assistance. Lim et al. [2], for instance, investigate the feasibility of using depth cameras and pressure mats in a balance training system for individuals with spinal cord injuries. A previous pilot study had shown the potential of a visual-feedback balance training (VFBT), coupled with closed-loop functional electrical stimulation (FES), to improve the standing balance in individuals with incomplete spinal-cord injury/disease [9, 10]. However, clinical implementation of such systems would be limited because of the required force plates, which are expensive and not easily accessible. Lim et al. [2] experimentally demonstrate that depth cameras and pressure mats can accurately track the body center of mass and center of pressure. As another example, Sabo et al. [7] demonstrate the responsiveness of a previously developed predictive vision-based machine learning model [11, 12] to measure changes in gait in response to medication and deep brain stimulation in individuals with Parkinson’s disease.

Following the success of ICAIR 2023, the conference will run as an annual event, each May in Toronto, Ontario, Canada. We plan to continue this collection in future, and each year invite a selection of some of the most exciting research projects presented at ICAIR.

Availability of data and materials

Not applicable.

References

  1. Marquez-Chin M, Saadatnia Z, Sun YC, et al. A dry polymer nanocomposite transcutaneous electrode for functional electrical stimulation. BioMed Eng OnLine. 2024;23:10.

    Article  Google Scholar 

  2. Lim D, Pei W, Lee JW, et al. Feasibility of using a depth camera or pressure mat for visual feedback balance training with functional electrical stimulation. BioMed Eng OnLine. 2024;23:19.

    Article  Google Scholar 

  3. Jawad T, Koh RGL, Zariffa J. Selective peripheral nerve recording using simulated human median nerve activity and convolutional neural networks. BioMed Eng OnLine. 2023;22:118.

    Article  Google Scholar 

  4. Kurbis AG, Kuzmenko D, Ivanyuk-Skulskiy B, et al. StairNet: visual recognition of stairs for human–robot locomotion. BioMed Eng OnLine. 2024;23:20.

    Article  Google Scholar 

  5. Basiri R, Manji K, LeLievre PM, et al. Protocol for metadata and image collection at diabetic foot ulcer clinics: enabling research in wound analytics and deep learning. BioMed Eng OnLine. 2024;23:12.

    Article  Google Scholar 

  6. Barzegar Khanghah A, Fernie G, Roshan Fekr A. Joint angle estimation during shoulder abduction exercise using contactless technology. BioMed Eng OnLine. 2024;23:11.

    Article  Google Scholar 

  7. Sabo A, Iaboni A, Taati B, et al. Evaluating the ability of a predictive vision-based machine learning model to measure changes in gait in response to medication and DBS within individuals with Parkinson’s disease. BioMed Eng OnLine. 2023;22:120.

    Article  Google Scholar 

  8. Simmatis LER, Robin J, Spilka MJ, et al. Detecting bulbar amyotrophic lateral sclerosis (ALS) using automatic acoustic analysis. BioMed Eng OnLine. 2024;23:15.

    Article  Google Scholar 

  9. Lee J, et al. A novel therapeutic tool for standing balance for individuals with incomplete spinal cord injury: a pilot study. Proceedings of the 22th Annual Conference of the International Functional Electrical Stimulation Society, Toronto. 2018.

  10. Houston DJ, et al. Functional electrical stimulation plus visual feedback balance training for standing balance performance among individuals with incomplete spinal cord injury: a case series. Front Neurol. 2020;11:680.

    Article  Google Scholar 

  11. Sabo A, et al. Assessment of Parkinsonian gait in older adults with dementia via human pose tracking in video data. J Neuroeng Rehabil. 2020;17:1–10.

    Article  Google Scholar 

  12. Sabo A, et al. Estimating Parkinsonism severity in natural gait videos of older adults with dementia. IEEE J Biomed Health Inform. 2022;26(5):2288–98.

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Contributions

All authors read and approved the final manuscript.

Corresponding author

Correspondence to Babak Taati.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Taati, B., Popovic, M.R. Special collection in association with the 2023 International Conference on aging, innovation and rehabilitation. BioMed Eng OnLine 23, 49 (2024). https://doi.org/10.1186/s12938-024-01243-x

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1186/s12938-024-01243-x