The development and evaluation of a fully automated markerless motion capture workflow.

This study presented a fully automated deep learning based markerless motion capture workflow and evaluated its performance against marker-based motion capture during overground running, walking and counter movement jumping. Multi-view high speed (200 Hz) image data were collected concurrently with marker-based motion capture (criterion data), permitting a direct comparison between methods. Lower limb kinematic data for 15 participants were computed using 2D pose estimation, our 3D fusion process and OpenSim based inverse kinematics modelling. Results demonstrated high levels of agreement for lower limb joint angles, with mean differences ranging "0.1° - 10.5° for hip (3 DoF) joint rotations, and 0.7° - 3.9° for knee (1 DoF) and ankle (2 DoF) rotations. These differences generally fall within the documented uncertainties of marker-based motion capture, suggesting that our markerless approach could be used for appropriate biomechanics applications. We used an open-source, modular and customisable workflow, allowing for integration with other popular biomechanics tools such as OpenSim. By developing open-source tools, we hope to facilitate the democratisation of markerless motion capture technology and encourage the transparent development of markerless methods. This presents exciting opportunities for biomechanics researchers and practitioners to capture large amounts of high quality, ecologically valid data both in the laboratory and in the wild.

The effects of orthotic heel lifts on Achilles tendon force and strain during running.

This study assessed the effects of orthotic heel lifts on Achilles tendon (AT) force and strain during running. Ten females ran barefoot over a force plate in three conditions: no heel lifts (NHL), with 12 mm heel lifts (12HL) and with 18 mm heel lifts (18HL). Kinematics for the right lower limb were collected (200 Hz). AT force was calculated from inverse dynamics. AT strain was determined from kinematics and ultrasound images of medial gastrocnemius (50 Hz). Peak AT strain was less for 18HL (5.5 ± 4.4%) than for NHL (7.4 ± 4.2%) (p = .029, effect size [ES] = 0.44) but not for 12HL (5.8 ± 4.8%) versus NHL (ES = 0.35). Peak AT force was significantly (p = .024, ES = 0.42) less for 18HL (2382 ± 717 N) than for NHL (2710 ± 830 N) but not for 12HL (2538 ± 823 N, ES = 0.21). The 18HL reduced ankle dorsiflexion but not flexion-extension ankle moments and increased the AT moment arm compared with NHL. Thus, 18HL reduced force and strain on the AT during running via a reduction in dorsiflexion, which lengthened the AT moment arm. Therefore, heel lifts could be used to reduce AT loading and strain during the rehabilitation of AT injuries.

The effects of a 30-min run on the mechanics of the human Achilles tendon.

Tendinous structures often exhibit reduced stiffness following repeated loading via static muscular contractions. The purpose of this study was to determine if human Achilles tendon (AT) stiffness is affected by the repeated loading experienced during running and if this affects normal muscle-tendon interaction. Twelve male participants (mean ± SD: age 27 ± 5 years, height 1.79 ± 0.06 m, mass 78.6 ± 8.4 kg) completed a 30 min run at 12 kmph on a treadmill. AT properties were determined before and after the run during a series of one-legged hops. During hopping and running, AT length data were acquired from a combination of ultrasound imaging (50 Hz) and kinematic data (200 Hz). AT force was estimated from inverse dynamics during hopping and AT stiffness was computed from plots of AT force and length. AT stiffness was not significantly different post run (pre 163 ± 41 N mm(-1), post 147 ± 52 N mm(-1), P > 0.05) and peak AT strain during the stance phase of running (calculated relative to AT length during standing) was similar at different time points during the run (3.5 ± 1.8% at 1 min, 3.2 ± 1.8% at 15 min and 3.8 ± 2% at 30 min). It was concluded that the loading experienced during a single bout of running does not affect the stiffness of the AT and that the properties of the AT are stable during locomotion. This may have implications for muscle fascicle behaviour and Achilles tendon injury mechanisms.

Could intra-tendinous hyperthermia during running explain chronic injury of the human Achilles tendon?

Chronic tendinopathy of the human Achilles tendon (AT) is common but its injury mechanism is not fully understood. It has been hypothesised that heat energy losses from the AT during running could explain the degeneration of AT material seen with injury. A mathematical model of AT temperature distribution was used to predict what temperatures the core of the AT could reach during running. This model required input values for mechanical properties of the AT (stiffness, hysteresis, cross-sectional area (CSA), strain during running) which were determined using a combination of ultrasound imaging, kinematic and kinetic data. AT length data were obtained during hopping and treadmill running (12 kmph) using ultrasound images of the medial gastrocnemius (50 Hz) and kinematic data (200 Hz). AT force data were calculated from inverse dynamics during hopping and combined with AT length data to compute AT stiffness and hysteresis. AT strain was computed from AT length data during treadmill running. AT CSA was measured on transverse ultrasound scans of the AT. Mean ± sd tendon properties were: stiffness = 176 ± 41 Nmm(-1), hysteresis =17 ± 12%, strain during running =3.5 ± 1.8% and CSA = 42 ± 8 mm(2). These values were input into the model of AT core temperature and this was predicted to reach at least 41°C during running. Such temperatures were deemed to be conservative estimates but still sufficient for tendon hyperthermia to be a potential cause of tendon injury.