Wearable Technology as an Objective Tool for Measuring Running Gait

Study Overview
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Brief Summary
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The investigators aim to use a repeated measures observational study utilising a battery of multimodal assessment tools (e.g., 3D motion capture, wearable technology) in order to validate the DANU Sports Socks. The investigators aim to recruit 40 recreational runners (male and female) from the North East of England. The multimodal battery assessment used in this study will compare metrics between gold-standard traditional assessment methods and more novel wearable technology methods. Following assessment of the validity and reliability of the DANU Sports Socks, the investigators will use the multi-modal sensor to quantify changes in running gait that may occur with injury, fatigue or performance level will permit quantification of running demands in a runner's natural environment, thereby providing insight into injury mechanisms and objective explanations for performance outcomes.

Detailed Description
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Background: Objective measurement of running gait is an important clinical tool for injury assessment and provides metrics that can be used to enhance performance. Running gait assessment has traditionally been performed using subjective observation or expensive laboratory-based objective technologies, such as 3D motion capture or force plates. However, recent developments in wearable technology allow for continuous monitoring and analysis of running mechanics in any environment, but technologies used for assessment must be valid and reliable. The objective of this study is to investigate the validity, reliability and subsequently the applied use of a commercial wearable technology (DANU Sports System) for running gait assessment. Following assessment of the validity and reliability of the DANU Sports Socks, the investigators use the multi-modal sensor to quantify changes in running gait that may occur with injury, fatigue or performance level will permit quantification of running demands in a runner's natural environment, thereby providing insight into injury mechanisms and objective explanations for performance outcomes. Methods: Laboratory Testing: With institutional ethics approval (Ref: 33358), laboratory testing will be conducted at the biomechanics laboratory Northumbria University, Newcastle upon Tyne, United Kingdom. Within the controlled laboratory environment, we will conduct a concurrent data collection with the multimodal, commercial, or research-grade wearables to determine their validation and reliability for running gait analysis compared to laboratory reference standards (3D motion capture and force plates). Participants: Within the laboratory testing 40 individuals will be recruited. Laboratory reference set-up: A 3D motion capture and force plate system will be used as the 'gold-standard' reference measures. Running procedures: All participants will run overground and, on a treadmill (Spirit fitness XT485). Participants will be provided with a standardised, neutral cushioning running shoe (Saucony Guide Runner) to wear during testing. For the overground segment, participants will run at a comfortable self-selected speed overground for 10m intermittently, where they will be asked to foot-strike two staggered force plates in the middle of the run ( 5m point). Practice trials will be performed prior to data collection to allow participants to adjust their start position to strike the force plates correctly. A total of five successful recordings for each of the left and right leg will be captured. For the treadmill segment, participants will be asked to run at five speeds, four of these speeds will be standardised (i.e., 8, 10, 12 and 14 km/hr) and one speed will be their self-selected speed. Self-selected speed will be determined by the participant's 5km personal best. The order of speed will be consistent across participants, starting at the slowest speed and progressing to the fastest, which is to ensure the safety of participants. Wearable device validity and reliability will be examined using intra-class correlation coefficients and Bland-Altman plots to compare to laboratory reference standards. Real-world environment testing: Data from the novel multimodal, commercial, and research-grade wearables will be collected within real-world environments to test the clinical / performance validity of the wearables (i.e., can they differentiate or provide meaningful data on relevant populations). Participants: Within the real-world environment testing 40 individuals, specifically novice/amateur (n=20) and expert/sub-elite (n=20) running performance level, based on their 5km running time (i.e., age graded performance %). Wearable location: Each participant will be equipped with the DANU Sports System (socks on both feet), two Axivity AX6 sensors attached to the shoelaces and two DorsaVi ViMove2 sensors on the tibia. Running procedures: All participants, regardless of performance level, will be asked to complete a 5km run on a standardised route in North-East England. The course will be run on a mixture of trail paths and concrete paths, with 174ft elevation gain throughout. Information about conditions (e.g., environment and shoes) and objective load data (e.g., time and pace) will be collected. Participants will wear their own running shoes. Running gait outcomes will include ground reaction forces, ground contact time, flight time, cadence, stride length, stride time and stride velocity. Conclusions: This exploratory observational study will assist with understanding the role that various grades of wearable devices (research-grade, commercial, novel multimodal) can have when assessing running gait inside and outside of the laboratory environment. In addition, it will provide evidence on the relationships between demographic factors, injury status, and performance level on objectively measured running gait outcomes. The outcomes of this study may better inform sports medicine and sports performance practice. Findings may shed light on the new ways of working with wearable technology for running gait analysis. Multimodal approaches may enhance understanding of running biomechanics and provide scalable, more objective assessment. Overall, wearable technology is rapidly becoming a feasible means to quantify running biomechanics in a more ecologically valid manner, with applications in sports medicine and sports performance. Regardless, practitioners should ensure that the use of wearable technology is evidence-based and fully investigate the accuracy, reliability, and value of any wearable device prior to incorporating them into practice.

Official Title
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Wearable Technology as an Objective Tool for Measuring Running Gait

Conditions
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Walking, Running, Gait, Gait Analysis

Participation Criteria
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Eligibility Criteria
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Inclusion Criteria: Aged 18 - 70 years. English as a first language or fluency. Able to run 5km without stopping. Take part in running of some form at least twice per week (e.g., 5km run). Exclusion Criteria: Medical history of disability that affects running gait safety or ability to follow instructions/tasks. Known illness or disease that would prevent their participation in strenuous physical activities (e.g., cardio-respiratory conditions or acute COVID-19). If the participant is unable to comply with the testing protocol, they will not be recruited.

Ages Eligible for Study
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Minimum Age: 18 Years
Maximum Age: 70 Years

Sexes Eligible for Study
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All

Accepts Healthy Volunteers
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Accepts Healthy Volunteers

Study Plan
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How is the study designed?
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Arms and Interventions

| Participant Group/Arm | Intervention/Treatment |
| --- | --- |
| Runners<br>Recreational runners will be recruited and assessed over one season (June 2021 to January 2024). Participants will be asked to complete a battery of sub-maximal walking and running trials. Participants will be stratified according to gender (males n≈20, and females n≈20). Participants may also be further stratified based on injury status (i.e. injury history and location) and performance level (i.e. 5km personal best time). | |

What is the study measuring?
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Primary Outcome Measures

| Outcome Measure | Measure Description | Time Frame |
| --- | --- | --- |
| Ground Contact Time | (ms, mean ± standard deviation) | Participants will be asked to attend two laboratory sessions 7 - 14 days apart. | 
| Tibial Acceleration | (g, mean ± standard deviation) | Participants will be asked to attend two laboratory sessions 7 - 14 days apart. | 
| Step Time | (ms, mean ± standard deviation) | Participants will be asked to attend two laboratory sessions 7 - 14 days apart. | 
| Step Length | (cm, mean ± standard deviation) | Participants will be asked to attend two laboratory sessions 7 - 14 days apart. | 
| Step Frequency | (n, mean ± standard deviation) | Participants will be asked to attend two laboratory sessions 7 - 14 days apart. | 
| Foot-strike Pattern | (°, mean ± standard deviation) | Participants will be asked to attend two laboratory sessions 7 - 14 days apart. | 
| Flight Time | (ms, mean ± standard deviation) | Participants will be asked to attend two laboratory sessions 7 - 14 days apart. | 

 Terms related to the study
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Keywords Provided by Centre Hospitalier Valida
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Gait, Walking, Running, Wearable Technology