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The ability to independently transfer into and out of a vehicle is essential for many wheelchair users to achieve driving independence. The purpose of the current study is to build upon the previous exploratory study that investigated the transfer strategies of wheelchair users by observing YouTube videos. This observational study videotaped five wheelchair users transferring from their wheelchairs into two research vehicles, a small and mid-size sedan that were equipped with a 50mm grid. The goal of this study was to use these videos and vehicle grids to precisely identify ingress and egress motions as well as “touch points” in a controlled setting with a small sample of five male wheelchair users. Using the videos from multiple different camera perspectives, the participants’ ingress and egress transfers were coded, documenting the touch points and step-by-step action sequences.

The ability to independently transfer into and out of a vehicle is essential for many wheelchair users to achieve driving independence. This paper presents the results of an exploratory study that investigated the transfer strategies of wheelchair users who drive from their driver’s seat and not from their wheelchair. The goal of this study was to identify typical ingress and egress motions as well as “touch points” of wheelchair users transferring into and out of the driver’s seat. While motion databases exist for the ingress and egress of able-bodied drivers, this study provides insight on drivers with physical disabilities. Twenty-five YouTube videos of wheelchair users who transferred into and out of their own sedans were analyzed.

While motorcycle safety frequently focuses on topics like helmet use and engineering aspects such as anti-lock braking systems, little research has investigated aging riders’ use of technologies (i.e., phones, navigation systems, etc.) or the characteristics of older riders (defined as above the age of 40) who use them. This study surveyed a convenience sample of typical motorcycle riders in the United States in order to provide an overview of the types of technologies that riders of different age groups use while riding, problems or concerns about those technologies, as well as rider demographics and riding habits. The sample included 97 riders (84 males and 13 females) between the ages of 20 and 71 years (M= 50.9, SD= 10.6) who were divided into three age groups (under 40 years, between 40 and 50 years, 50 years and older).