PhD Pinboard: Analysing Running Gait Analysis across Wearable Technologies
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- Aug 13
- 9 min read
Updated: Sep 16
This PhD Pinboard article by Rachel Mason explores the application of various wearable technologies for gait running analysis, providing key considerations for scientists and users alike.
I’m Rachel Mason – a Senior Research Associate at Lancaster University and Event Technician at SEIKO Timing Ltd. I recently completed my PhD at Northumbria University, in collaboration with DANU Sports.
Why does this research matter?
Running is one of the most widely practiced physical activities across the globe, both as a recreational pursuit and as a fundamental component of many sports disciplines [1]. Traditionally, running gait analysis was confined to specialised sports science laboratories and elite clinical settings [2]. However, advancements in wearable technology have made gait analysis increasingly accessible.
Wearables such as sensor-embedded socks, shin-mounted inertial measurement units (IMUs), and smartphone applications offering real-time feedback are now available to a broader population of runners.
Despite this expansion, there remains a significant gap in the literature regarding their validity, reliability, and practical application [3]. Different categories of wearables often receive varying levels of testing. Commercial wearables, for example, may be launched with little or no formal validation, while research-grade devices developed by academic institutions are typically subjected to more rigorous testing, but not tested on the specific populations or in real-world environments [3].
To address these gaps, my PhD thesis, titled "Wearable Technology for Objective Running Gait Analysis" aimed to evaluate the validity, reliability, and application of three categories of wearables, research-grade (Axivity Ax6), commercially available (ViMove2), and a novel multi-modal system (DANU Sports) specifically for running gait assessment (see Figure 1 below).
The study follows an evidence-based protocol (V3 Model) designed to support the adoption of wearables that are "fit-for-purpose": the utility of any wearable can only be assessed once we establish that its data are valid and reliable for the intended use [4].
Each was tested for:
analytical validity: accuracy in lab conditions
performance validity: usefulness in real-world runs
usability: how runners felt about wearing and using them.
Key Findings
Lab Testing
In controlled lab conditions, both the Axivity AX6 and DANU System performed strongly in measuring key metrics like Ground Contact Time (GCT), Swing Time (SwT) and Stride Time (ST). The ViMove2 system, while user-friendly, showed weaker agreement, especially at slower speeds and among female runners. The table below provides a comparison of the key characteristics of the wearables examined throughout my PhD [5-8].
This raises an important issue: not all wearables are created equal, especially when it comes to populations with different biomechanics. Also, there’s a trade-off: research-grade wearables like the AX6 require specialist knowledge to set up and analyse. They're great in the lab, but harder to use in the field.
Real-World Runs: The 5K Test
To test how these wearables perform outside the lab, the research included a 5km outdoor run with 70 participants, examining the Axivity Ax6 and the DANU Sports system. This added real-world complexity: uneven terrain, weather, and self-selected speeds.
Despite some technical hiccups (Bluetooth dropouts, sensor slippage), both the DANU System and Axivity AX6 showed strong reliability. Interestingly, the DANU System recorded a reduction in GCT over the run, potentially indicating improved efficiency while the AX6 showed increases, which might point to fatigue (Figure 2).
So, which one was right? That depends on how you interpret the data. But what’s clear is that even small differences between systems can change how we understand a runner’s gait, and whether they’re improving, plateauing, or heading toward injury.
This demonstrates that wearables are not interchangeable. Their algorithms, sensor placements, and data handling differ, which means practitioners must know exactly what they’re using and why.
Usability: Runners Speak Up
You can build the most accurate wearable in the world, but if it’s uncomfortable, awkward, or confusing to use, no one will wear it. Yet when it comes to running gait analysis, are wearables actually being used in the way we expect? More importantly, do runners and practitioners find them useful?
We surveyed 50 runners and ran focus groups with 15 practitioners, including coaches, physiotherapists, and sports scientists, to get a clearer picture of where wearable gait tech stands in the real world. Here's what we found:
Most Runners Are Interested, But Cautious: From the survey, we saw that most runners were curious about wearable tech. In fact, over 80% had used some form of wearable in the past year, mostly GPS watches or fitness trackers. When asked about using wearables specifically for running gait analysis, the interest remained strong, but it came with conditions.
Runners rated accuracy, comfort, and ease of interpretation as the top three priorities. Over 70% said they’d consider using gait-specific wearables if the data was clear and directly applicable to their training or injury prevention.
But here’s the catch: only a small percentage had used wearables to analyse gait. For most, the perceived complexity or lack of clarity in the data was a barrier.
Practitioners Are Interested, But Strategic: Focus Groups allowed us to delve deeper. We asked experienced practitioners about their views on wearables for running gait analysis.
Their perspectives were nuanced. When it comes to wearables, comfort is key. Practitioners unanimously agreed: “If it’s not comfortable, they’re not gonna wear it.” Design matters, not just in terms of aesthetics, but in how and where wearables are worn. Whether sensors sit on the foot, trunk, or wrist depends on the metrics being captured, and poorly secured hardware can compromise data integrity. A seamless connection between hardware, software, and user interface was seen as essential for both usability and accuracy.
But even the best-designed device is only as good as the insights it delivers. Practitioners warned of “too much data that’s not always meaningful,” especially mid-race or in high-pressure environments. Context is necessary, tailoring insights to the individual athlete, training phase, or rehab protocol. Wearables were viewed as valuable tools for longitudinal tracking, strength and conditioning, and real-world clinical assessments, “adding context you just don’t get in a clinical exam.”
Still, concerns remain. Accuracy matters more in elite settings where small margins count, and there were clear worries around “data privacy,” especially when third-party apps get involved. Cost was another sticking point: most favoured “affordable devices with essential features” over expensive systems offering more than was needed.
In short, wearables must strike a delicate balance - reliable, intuitive, athlete-centred, and above all, wearable.
How can we apply these findings in practice?
Based on the findings to get the most of the wearables, key things to consider are:
1. Balance Accuracy and Accessibility
High-end wearables must become easier to use without losing precision (see figure 3 below). That might mean better mobile apps, automated feedback, or cloud-based analytics that simplify the science.
2. Build for the User, Not the Engineer
Comfort, fit, and simplicity aren’t extras, they’re essential. Wearables need to adapt to different body types and gait patterns with breathable fabrics, adjustable fits, and flexible sensor placement. If it’s uncomfortable or confusing, it won’t get used, no matter how accurate it is.
3. Make Data Make Sense and Actionable
The best wearable is one that helps translate data into decisions: change a shoe, adjust cadence, monitor fatigue. More intuitive dashboards and simplified visualisations will help bridge the gap between data and decision-making.
4. Prioritise Privacy and Cost
Runners are increasingly aware of data privacy and the cost of subscription-based models. Companies need to build trust, not just collect data.
5. Standardise and Compare
Currently, there’s no universal standard for wearable gait analysis. That means comparing systems is tough and trusting them even harder. Industry-wide benchmarks, validated protocols, and shared datasets could help build credibility.
6. Know Your Tools
Don’t just buy what’s popular. Ask for validation studies. Compare outputs across wearables. Know what each sensor measures and what it doesn’t.
7. Tailor to Your Use Case
For detailed lab assessments? Go with something like the Axivity AX6. For on-the-ground monitoring over time? The DANU System, once refined, holds promise, especially for rehab and progression tracking.
Final Thoughts
The future of running gait analysis is wearable, but that future isn’t evenly distributed. While systems like the DANU show what’s possible, the road to mainstream adoption will require collaboration between researchers, developers, athletes, and clinicians. It’s not just about collecting data. It’s about collecting the right data in a way that’s accurate, accessible, and actionable.
Overall, the best wearable isn’t the one with the most sensors. It’s the one that helps you take the next step, smarter.
Frequently Asked Questions (FAQs)
Can wearable technology replace lab-based assessments for running gait?
Not entirely, but it’s getting closer. Wearables like the DANU System and Axivity AX6 have shown strong accuracy and reliability in measuring key metrics like GCT, SWT and ST. While lab-based systems remain the gold standard for detailed biomechanical analysis, wearables offer a portable, affordable, and practical way to assess gait in real-world environments. Think of them as the bridge between elite lab setups and everyday training.
Is there one “best” wearable technology for runners?
No. The best wearable depends on your goals, whether you seek something with lab precision, reliability, real-world tracking, comfort and usability.
How should I interpret data obtained from wearable technology?
Many runners in our study found the data useful but hard to interpret. Raw numbers like “GCT = 186ms” mean little without context. The best wearables simplify the experience, offering visual dashboards, clear trends, and real-world training takeaways. If your wearable needs an expert to decode, it’s not doing its job.
Do I need to wear wearable technology on every run?
No, but regular use has benefits. Many practitioners use wearables during key assessment periods (e.g., return-to-run, baseline). If comfort and usability permit, then the wearable could be worn every day to allow for the user to create their own normative ranges, and potentially detect risk of injury or overtraining, as well as track performance indicators.
References
[1] Andersen JJ. The State of Running 2019 [Internet]. RunRepeat; 2019 [cited 2025 Jun 20]. Available from: https://runrepeat.com/state-of-running
[2] Wang L, Hu W, Tan T. Recent developments in human motion analysis. Pattern Recognit. 2003 Mar;36(3):585–601. doi:10.1016/S0031-3203(02)00100-0.
[4] Goldsack JC, Coravos A, Bakker JP, Bent B, Dowling AV, Fitzer-Attas C, et al. Verification, analytical validation, and clinical validation (V3): the foundation of determining fit-for-purpose for Biometric Monitoring Technologies (BioMeTs). NPJ Digit Med. 2020 Apr 14;3(1):55. doi:10.1038/s41746-020-0260-4.
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