Effects of natural shoe wear on traction performance: a longitudinal study.

Footwear outsole design is an important factor for shoe-floor friction and for preventing slipping. Shoes with small, uniformly-separated tread blocks (often included on slip-resistant shoes) have decreased slip risk due to their increased friction and better under-shoe fluid drainage. However, these traction performance metrics (friction and fluid drainage) diminish with wear. This study quantifies shoe traction performance in response to natural wear and compares the relationship between common wear metrics: time, distance walked, and worn region size (WRS). Participants wore two pairs of shoes in the workplace for up to 11 months and the distance walked was tracked with a pedometer. After each month of wear, traction performance and WRS of each shoe were measured. Traction performance was quantified by the under-shoe available coefficient of friction and fluid force during a simulated slip condition. Increased wear (months worn, distance walked, and WRS) was associated with decreased traction performance. A WRS of 800 mm2 was associated with reductions in friction of 16-38% and increases in fluid force by 286-528%. Three and six months of wear were associated with WRS values of 251 mm2 and 462 mm2 and distances of 203 km and 519 km, respectively. A walking distance of 500 km was associated with a WRS of 406 mm2. This study showed that all these wear metrics are good indicators of shoe traction performance loss. Thus, the most practical metric in a particular application can be selected. We argue that WRS may be the best indicator due to variations in wear rate from the user and environment. Therefore, tracking footwear usage and monitoring outsole wear can aid in shoe replacement recommendations to reduce slips and falls.

Big data vs accurate data in health research: Large-scale physical activity monitoring, smartphones, wearable devices and risk of unconscious bias.

Fundamental to the advancement of scientific knowledge is unbiased, accurate and validated measurement techniques. Recent United Nations and landmark Nature publications highlight the global uptake of mobile technology and the staggering potential for big data to encourage people to be physically active and to influence health policy. However, concerns exist about inconsistencies in smartphone health apps. Big data has many benefits, but noisy data may lead to wrong conclusions. In reaction to the increasing availability of low quality data; we call for a rigorous debate into the validity of substituting big data for accurate data in health research. We evaluated the step counting accuracy of a smartphone app previously used by 717,527 people from 111 countries. Our new data (from 48 participants; aged 21-59 years; body mass index 17.7-33.5 kg/m2) revealed significant (15-66%) undercounting by Apple phones. In contrast to the generally positive performances of wearable devices for stereotypical treadmill like walking, we observed extraordinarily large (0-200% of steps taken) error ranges for both Android and Apple phones. Unconscious bias (developers' perceptions of usual behaviour) may be embedded into many unvalidated smartphone apps. Consumer-grade wearable devices appear unsuitable to detect steps in people with slow, short or non-stereotypical gait patterns. Specifically, there is a risk of systematically undercounting the steps by obese people, females or people from different ethnic groups resulting in biases when reporting associations between physical inactivity and obesity. More research is required to develop smartphone apps suitable for all people of the heterogeneous global population.