Effects of Mobile Technology Use on Walking. (September 2014) - Perlmutter, Sam; Cades, David M.; Heller, Michelle F.; Giachetti, Robert; Arndt, Steven R.; Sala, Joseph B.
Objective: The goal of this study was to evaluate the efficacy of combining cognitive and kinematic measurements to study the effects of mobile technology use on walking.Background: It has previously been shown that being distracted by a cell phone, or other mobile technology, can have a negative impact on activities such as crossing a street and may also alter gait patterns. While the negative effects of cell phone use on driving have been extensively studied, research into the distracted pedestrian is lacking. Method: Twelve adults walked down an office corridor without using a cell phone (BASELINE) and while performing a secondary cognitive task under two conditions. The secondary task involved answering simple multiplication problems through either text messaging (TEXT) or while talking on the phone (VOICE). Participants' gait patterns were measured using a GAITRite gait pad LEGSys wearable wireless sensors.Results: In the TEXT condition, participants walked more slowly and had shorter strides. There was no significant difference between the VOICE and BASELINE condition. Participants answered more multiplication problems per trial in the VOICE condition as compared to the TEXT condition. Excluding typos, error rates for the multiplication problems were not significantly different between the TEXT and VOICE conditions.Conclusion: This study demonstrated that the effect of reading and responding to text messages on gait was able to be detected utilizing methods that do not require strictly sterile laboratory settings. This serves as a proof of concept for researchers to bring the study and evaluation of distracted walking into the naturalistic environments in which it actually occurs.Application: This proof of concept will serve as a roadmap towards moving the study of gait and distraction from simple observational studies in naturalistic environments to specific quantitative analysis of people performing real world tasks in real world settings.