Walking is regulated by environmental temperature

A singular, broadly-applicable model for estimating on- and off-path walking travel rates using airborne lidar data

Accurate prediction of walking travel rates is central to wide-ranging applications, including modeling historical travel networks, simulating evacuation from hazards, evaluating military ground troop movements, and assessing risk to wildland firefighters. Most of the existing functions for estimating travel rates have focused on slope as the sole landscape impediment, while some have gone a step further in applying a limited set of multiplicative factors to account for broadly defined surface types (e.g., "on-path" vs. "off-path"). In this study, we introduce the Simulating Travel Rates In Diverse Environments (STRIDE) model, which accurately predicts travel rates using a suite of airborne lidar-derived metrics (slope, vegetation density, and surface roughness) that encompass a continuous spectrum of landscape structure. STRIDE enables the accurate prediction of both on- and off-path travel rates using a single function that can be applied across wide-ranging environmental settings. The model explained more than 80% of the variance in the mean travel rates from three separate field experiments, with an average predictive error less than 16%. We demonstrate the use of STRIDE to map least-cost paths, highlighting its propensity for selecting logically consistent routes and producing more accurate yet considerably greater total travel time estimates than a slope-only model.

Modified stepping behaviour during outdoor winter walking increases resistance to forward losses of stability

Healthy humans are proficient at maintaining stability when faced with diverse walking conditions, however, the control strategies that lead to this proficiency are unclear. Previous laboratory-based research has predominantly concluded that corrective stepping is the main strategy, but whether this finding holds when facing everyday obstacles outside of the laboratory is uncertain. We investigated changes in gait stability behaviour when walking outdoors in the summer and winter, hypothesizing that as ground conditions worsened in the winter, the stepping strategy would be hindered. Stability would then be maintained through compensatory strategies such as with ankle torques and trunk rotation. Data was collected in the summer and winter using inertial measurement units to collect kinematics and instrumented insoles to collect vertical ground reaction forces. Using the goodness of fit for a multivariate regression between the centre of mass state and foot placement we found that, counter to our hypothesis, stepping was not hindered by winter conditions. Instead, the stepping strategy was modified to increase the anterior-posterior margin of stability, increasing the resistance to a forward loss of stability. With stepping being unhindered, we did not observe any additional compensation from the ankle or trunk strategies.

Carrying children, groceries, and water across varying terrain: Changes in gait and comfortable walking speed

BACKGROUND

Carrying items of substantial weight and value in one's arms while traversing challenging terrain is a common task that requires considerable care. Carrying valuable (e.g., child) or variable (e.g., water) items, compared to stable ones (e.g., groceries) demands increased coordination, and is likely to lead to slower comfortable walking speed (CWS) and altered gait mechanics, especially on difficult terrain.

RESEARCH QUESTION

How are gait parameters altered by carrying items of substantial weight and varying value and dynamics across more and less demanding terrain?

METHODS

In two experiments, participants carried their child, an equally weighted sack of groceries, or an open bucket of water in the same manner across level floor and across uneven stairs of varying heights with gaps between them. Kinematics were assessed for both terrains; kinetics were measured for one step up and one step down on stairs.

RESULTS

Mixed models ANOVAs with repeated measures revealed that CWS on uneven stairs was approximately 65 % of CWS for level floor, regardless of the item carried. Step-to-step coefficients of variation for step length and CWS were also greater. Water was carried most slowly, with shorter steps on level floor and reduced accelerations on uneven stairs. CWS with children and groceries did not differ.

SIGNIFICANCE

Carrying items of weight and worth with varying dynamics across more and less challenging terrain illustrates the ecological complexity of walking. Terrain requiring greater flexibility, strength, and coordination reduced CWS substantially, a complexity-speed tradeoff. More variable, difficult to control items altered CWS and other gait patterns regardless of terrain difficulty, suggesting terrain and item dynamics contributed independently to gait adjustments. More valuable items were not carried more slowly than less valuable ones. Carrying tasks deserve greater attention in research and clinical assessment.

Association between daily life walking speed and frailty measured by a smartphone application: a cross-sectional study

OBJECTIVES

To assess whether frailty can be assessed using a smartphone and whether daily walking speed (DWS) is associated with frailty.

DESIGN

Cross-sectional study.

SETTING

Three prefectures (Kanagawa, Saitama and Tokyo) in Japan.

PARTICIPANTS

The study enrolled 163 participants (65 in the robust group, 69 in the prefrailty group and 29 in the frailty group) by sending letters to house owners aged≥55 years.

PRIMARY AND SECONDARY OUTCOME MEASURES

The participants downloaded the DWS measurement application on their smartphones, which measured the daily walking (DW) parameters (DWS, step length and cadence) and the Kihon checklist for frailty assessment. The differences in the DW parameters between the robust, prefrailty and frailty groups were examined using one-way analysis of variance. We conducted logistic regression analysis for the Crude model (each DW parameter), model 1 (adjusted for the number of steps) and model 2 (model 1+age, sex and the number of chronic diseases).

RESULTS

DWS was marginally significantly slower in the frailty group than in the prefrailty and robust group (robust 1.26 m/s vs prefrailty 1.25 m/s vs frailty 1.19 m/s, p=0.060). Step length was significantly smaller in the frailty group than in the robust group (robust 66.1 cm vs prefrailty 65.9 vs frailty 62.3 cm, p<0.01). Logistic regression analysis for the three models revealed that DWS was significantly associated with frailty.

CONCLUSIONS

DWS measured using the smartphone application was associated with frailty. This was probably due to the shorter step length and body height seen in frail individuals.

The influence of weather and temperature on pedestrian walking characteristics on the zigzag bridge

With the increasing number of tourists in recent years, ensuring the safety of visitors in tourist attractions has become an enormous challenge for safety management. At present, many experiments have been conducted to study pedestrian dynamics, but empirical data on tourists' movement state under different weather conditions are still few. Therefore, a series of field experiments were conducted to analyze the effect of external weather and temperature on pedestrians' movement characteristics. The results show that pedestrians are more concentrated in the middle and inner tracks during the turning process to seek the shortest path on rainy days. Moreover, it is found that pedestrians speed up under the conditions with low (below 10 °C) and high (over 30 °C) temperatures. The average speed of pedestrians is 0.677 m/s as the temperature is below 0 °C, which is much higher than the average speed of pedestrians in other temperature ranges. In addition, the speed of pedestrians changed more dramatically under the low-temperature conditions. It is hoped that this research can provide a reference for crowd control and rational design of pedestrian facilities.

Metadata Framework to Support Deployment of Digital Health Technologies in Clinical Trials in Parkinson's Disease

Sensor data from digital health technologies (DHTs) used in clinical trials provides a valuable source of information, because of the possibility to combine datasets from different studies, to combine it with other data types, and to reuse it multiple times for various purposes. To date, there exist no standards for capturing or storing DHT biosensor data applicable across modalities and disease areas, and which can also capture the clinical trial and environment-specific aspects, so-called metadata. In this perspectives paper, we propose a metadata framework that divides the DHT metadata into metadata that is independent of the therapeutic area or clinical trial design (concept of interest and context of use), and metadata that is dependent on these factors. We demonstrate how this framework can be applied to data collected with different types of DHTs deployed in the WATCH-PD clinical study of Parkinson's disease. This framework provides a means to pre-specify and therefore standardize aspects of the use of DHTs, promoting comparability of DHTs across future studies.