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Accuracy of training recommendations based on a treadmill multistage incremental exercise test
(2018)
Competitive runners will occasionally undergo exercise in a laboratory setting to obtain predictive and prescriptive information regarding their performance. The present research aimed to assess whether the physiological demands of lab-based treadmill running (TM) can simulate that of over-ground (OG) running using a commonly used protocol. Fifteen healthy volunteers with a weekly mileage of ≥ 20 km over the past 6 months and treadmill experience participated in this cross-sectional study. Two stepwise incremental tests until volitional exhaustion was performed in a fixed order within one week in an Outpatient Clinic research laboratory and outdoor athletic track. Running velocity (IATspeed), heart rate (IATHR) and lactate concentration at the individual anaerobic threshold (IATbLa) were primary endpoints. Additionally, distance covered (DIST), maximal heart rate (HRmax), maximal blood lactate concentration (bLamax) and rate of perceived exertion (RPE) at IATspeed were analyzed. IATspeed, DIST and HRmax were not statistically significantly different between conditions, whereas bLamax and RPE at IATspeed showed statistical significance (p < 0.05). Apart from RPE at IATspeed, IATspeed, DIST, HRmax and bLamax strongly correlate between conditions (r = 0.815–0.988). High reliability between conditions provides strong evidence to suggest that running on a treadmill are physiologically comparable to that of OG and that training recommendations and be made with assurance.
Low back pain (LBP) is a leading cause of activity limitation. Objective assessment of the spinal motion plays a key role in diagnosis and treatment of LBP. We propose a method that facilitates clinical assessment of lower back motions by means of a wireless inertial sensor network. The sensor units are attached to the right and left side of the lumbar region, the pelvis and the thighs, respectively. Since magnetometers are known to be unreliable in indoor environments, we use only 3D accelerometer and 3D gyroscope readings. Compensation of integration drift in the horizontal plane is achieved by estimating the gyroscope biases from automatically detected initial rest phases. For the estimation of sensor orientations, both a smoothing algorithm and a filtering algorithm are presented. From these orientations, we determine three-dimensional joint angles between the thighs and the pelvis and between the pelvis and the lumbar region. We compare the orientations and joint angles to measurements of an optical motion tracking system that tracks each skin-mounted sensor by means of reflective markers. Eight subjects perform a neutral initial pose, then flexion/extension, lateral flexion, and rotation of the trunk. The root mean square deviation between inertial and optical angles is about one degree for angles in the frontal and sagittal plane and about two degrees for angles in the transverse plane (both values averaged over all trials). We choose five features that characterize the initial pose and the three motions. Interindividual differences of all features are found to be clearly larger than the observed measurement deviations. These results indicate that the proposed inertial sensor-based method is a promising tool for lower back motion assessment.