Spatio-temporal gait analysis based on human-smart rollator interaction

The ability to walk is typically related to several biomechanical components that are involved in the gait cycle (or stride), including free mobility of joints, particularly in the legs; coordination of muscle activity in terms of timing and intensity; and normal sensory input, such as vision and vestibular system. As people age, they tend to slow their gait speed, and their balance is also affected. Also, the retirement from the working life and the consequent reduction of physical and social activity contribute to the increased incidence of falls in older adults. Moreover, older adults suffer different kinds of cognitive decline, such as dementia or attention problems, which also accentuate gait disorders and its consequences. In this paper we present a methodology for gait identification using the on-board sensors of a smart rollator: the i-Walker. This technique provides the number of steps performed in walking exercises, as well as the time and distance travelled for each stride. It also allows to extract spatio-temporal metrics used in medical gait analysis from the interpretation of the interaction between the individual and the i-Walker. In addition, two metrics to assess users’ driving skills, laterality and directivity, are proposed.Peer ReviewedPostprint (author's final draft

AI based fall management services: the role of the i-Walker in I-DONTFALL

Falls are a major international public health challenge because of the myriad effects on older individuals: direct physical and psychological injury; fear of falling and activity limitation; reduced social participation and quality of life; increased dependence; and because of the economic impact on health and social care providers. In nowadays ageing society, many people require assistance for safe pedestrian mobility. In some cases, assistive devices require a certain degree of autonomy when the persons’ disabilities difficult manual control. Our aim is to develop an open and innovative reference architecture, based upon ontologies and agent services, that will allow plug and play and cost-effective interconnection of existing and new services in all domains required for the independent and autonomous living of the elderly and their enhanced Quality of Life (QoL)