Automatic classification of gait patterns using a smart rollator and the BOSS model

Nowadays, the risk of falling in older adults is a major concern due to the severe consequences it brings to socio-economic and public health systems. Some pathologies cause mobility problems in the aged population, leading them to fall and, thus, reduce their autonomy. Other implications of ageing involve having different gait patterns and walking speed. In this paper, a non-invasive framework is proposed to study gait in elder people using data collected by a smart rollator, the i-Walker. The analysis presented in this article uses a feature extraction method and a spectral embedding to represent the information and Bayesian clustering for the knowledge discovery. The algorithm considers raw data from the i-Walker sensors along with the calculated walking speed of each individual, which has been already used in clinical studies to assess physical and cognitive status of older adults. The results obtained demonstrate that the proposed analysis has the potential to separate in clusters the people of the two groups of interest: young people and geriatric.Peer ReviewedPostprint (author's final draft

Advances in Human-Robot Interaction

Rapid advances in the field of robotics have made it possible to use robots not just in industrial automation but also in entertainment, rehabilitation, and home service. Since robots will likely affect many aspects of human existence, fundamental questions of human-robot interaction must be formulated and, if at all possible, resolved. Some of these questions are addressed in this collection of papers by leading HRI researchers

Feature Papers "Age-Friendly Cities & Communities: State of the Art and Future Perspectives"

The "Age-Friendly Cities & Communities: States of the Art and Future Perspectives" publication presents contemporary, innovative, and insightful narratives, debates, and frameworks based on an international collection of papers from scholars spanning the fields of gerontology, social sciences, architecture, computer science, and gerontechnology. This extensive collection of papers aims to move the narrative and debates forward in this interdisciplinary field of age-friendly cities and communities

Investigation and Quantification of FES Exercise – Isometric Electromechanics and Perceptions of Its Usage as an Exercise Modality for Various Populations

Functional Electrical Stimulation (FES) is the triggering of muscle contraction by use of an electrical current. It can be used to give paralyzed individuals several health benefits, through allowing artificial movement and exercise. Although many FES devices exist, many aspects require innovation to increase usability and home translation. In addition, the effect of changing electrical parameters on limb biomechanics is not entirely understood; in particular with regards to stimulation duty cycle. This thesis has two distinct components. In the first (public health component), interview studies were conducted to understand several issues related to FES technology enhancement, implementation and home translation. In the second (computational biomechanics component), novel signal processing algorithms were designed that can be used to measure mechanical responses of muscles subjected to electrical stimulation. These experiments were performed by changing duty cycle and measuring its effect on quadriceps-generated knee torque. The studies of this thesis have presented several ideas, toolkits and results which have the potential to guide future FES biomechanics studies and the translatability of systems into regular usage for patients. The public health studies have provided conceptual frameworks upon which FES may be used in the home by patients. In addition, they have elucidated a range of issues that need to be addressed should FES technology reach its true potential as a therapy. The computational biomechanics studies have put forward novel data analysis techniques which may be used for understanding how muscle responds to electrical stimulation, as measured via torque. Furthermore, the effect of changing the electrical stimulation duty cycle on torque was successfully described, adding to an understanding of how electrical stimulation parameter modulation can influence joint biomechanics

Home & place making after stroke:Exploring the gap between rehabilitation and living environment

This thesis addresses the question why many stroke survivors, even when they have received optimal treatment in the rehabilitation center, fall into a black hole when they are at home. The goal is twofold: 1) to gain a better understanding of the experienced gap between the rehabilitation and living environment of stroke survivors, and 2) to help improve the transfer from the rehabilitation to the living environment with help of scientific knowledge. This thesis shows that to improve rehabilitation care till into the own living environment, available evidence-based knowledge should be enriched with practical knowledge of rehabilitation professionals and experience-based knowledge from stroke survivors and caregivers. Interviews with stroke survivors reveal that ‘being at home’ does not equal ‘feeling at home’. Resuming life at home after a stroke is very different from recovering in the rehabilitation environment. In order to better understand the problems, other theory is needed than only theory from rehabilitation medicine. This thesis provides a new theoretical perspective for rehabilitation medicine. We have viewed stroke survivors’ and their caregivers’ experiences through a socio-spatial lens. This results in a shift in focus from functional recovery to identity confusion and feeling at home at important places after stroke. It is recommended to have one professional in outpatient and home rehabilitation, who acts as a coach, and assists stroke survivors and caregivers in rebuilding meaningful and interconnected relationships with their lives, place by place

Proceedings of the 2018 Canadian Society for Mechanical Engineering (CSME) International Congress

Published proceedings of the 2018 Canadian Society for Mechanical Engineering (CSME) International Congress, hosted by York University, 27-30 May 2018

Medical-Data-Models.org:A collection of freely available forms (September 2016)

MDM-Portal (Medical Data-Models) is a meta-data repository for creating, analysing, sharing and reusing medical forms, developed by the Institute of Medical Informatics, University of Muenster in Germany. Electronic forms for documentation of patient data are an integral part within the workflow of physicians. A huge amount of data is collected either through routine documentation forms (EHRs) for electronic health records or as case report forms (CRFs) for clinical trials. This raises major scientific challenges for health care, since different health information systems are not necessarily compatible with each other and thus information exchange of structured data is hampered. Software vendors provide a variety of individual documentation forms according to their standard contracts, which function as isolated applications. Furthermore, free availability of those forms is rarely the case. Currently less than 5 % of medical forms are freely accessible. Based on this lack of transparency harmonization of data models in health care is extremely cumbersome, thus work and know-how of completed clinical trials and routine documentation in hospitals are hard to be re-used. The MDM-Portal serves as an infrastructure for academic (non-commercial) medical research to contribute a solution to this problem. It already contains more than 4,000 system-independent forms (CDISC ODM Format, www.cdisc.org, Operational Data Model) with more than 380,000 dataelements. This enables researchers to view, discuss, download and export forms in most common technical formats such as PDF, CSV, Excel, SQL, SPSS, R, etc. A growing user community will lead to a growing database of medical forms. In this matter, we would like to encourage all medical researchers to register and add forms and discuss existing forms