With the further advancement of sensor technologies and data analyzing techniques, micro-electro-mechanical sensors (MEMS) have become useful tools for biomechanical research and clinical practice [1
]. It has been reported that these wearable motion sensors are an inexpensive alternative to optoelectronic systems and force plates, that they are simple to handle, cost-effective, and are suitable for field measurements [2
]. When using these sensors, spatio-temporal and kinetic parameters during walking and running can be analyzed in clinical as well as in sportive applications. For kinetic measurements, for example, when investigating the impact loads on lower limbs during running under various conditions (e.g., footwear conditions or the influence of fatigue), the peak tibial acceleration (PTA) was examined by some authors using MEMS [7
]. Thereby, unidirectional accelerations along the longitudinal axis of the tibia, as well as medio-lateral and anterior-posterior accelerations of the tibia were examined. Furthermore, the determination of stride frequency, of walking or running velocity (runVel), and of stride length (strLen) have also been the focus of research that utilizes MEMS [21
]. To investigate these biomechanical parameters, individually configured sensors or commercially available inertial measurement units (IMUs: e.g., Shimmer, Achillex, or XSens) were used, which combine accelerometers and gyroscopes. In this context, Provot et al. [26
] compared a calibrated industrial accelerometer (considered as the gold standard) to an IMU accelerometer in two tests: (a) on a shaker, and (b) on the distal anteromedial aspect of the subject’s tibia during running at 3.33 m/s. They concluded that IMUs can be used for valid measurements of tibial acceleration during running.
Besides the different sensor types, sensor locations, and the various sampling rates, sensors with considerably different accelerometer operating ranges (ORs) have also been used. When investigating walking or running, some studies used ORs between ±2 and ±70 g, with g being the acceleration of gravity [27
]. However, high accelerations act on the sensor in vertical and anterior–posterior directions during the swing phase and in the first 50 ms after foot strike [11
]. These accelerations can distinctly exceed the gravitational acceleration of 1 g. For instance, vertical accelerations of 24.62 ± 4.1 g were measured with a heel-mounted IMU accelerometer during heel strike, when running at 3.5 ± 0.1 m/s in a neutral running shoe (PUMA FAAS 500) [32
]. If the accelerations exceeded the accelerometer OR, a lower accuracy and an underestimated variability of biomechanical parameters derived from accelerometer signals could result. In this context, Ziebart et al. [33
] investigated the influence of accelerometer OR and of a sampling rate on peak acceleration during seven jumping tasks. They used a tri-axial accelerometer (Model 7267A, Endevco Corporation, San Juan Capistrano, CA, USA) with a high OR of ±260 g as the reference and compared the peak accelerations with two commercially available tri-axial accelerometers with an OR of ±6 g (device1: ActiGraph GT3X+, ActiGraph LLC, Pensacola, FL, USA and device2: X6-2mini, Gulf Coast Data Concepts, Waveland, MS, USA). They found that the peak impact acceleration was underestimated by up to 35%. Furthermore, the underestimation error was greater for tasks with a greater impact acceleration.
It is currently still unclear whether, and to what extent, high accelerations can influence the accuracy of running parameters when exceeding the accelerometers’ OR. However, this information is necessary to determine whether differences in the investigated biomechanical parameters strLen, runVel, and in the PTA between conditions are caused by measurement errors due to an accelerometer OR that is too low, or by the investigated conditions themselves.
In addition, the sensor signal characteristics of the IMU accelerometer, which is affixed to the heel cup of a running shoe, can be influenced by the midsole stiffness of footwear [5
]. The authors found that a decreasing midsole stiffness resulted in an increasing delay in specific signal characteristics, when determining the time of foot touchdown. At this time, it is still unclear whether the accuracies of strLen and runVel are also influenced by altering acceleration signal characteristics due to a change in midsole stiffness.
Since acceleration variables are related to running injuries, information about whether the ORs influences running parameters is highly relevant and could assist coaches, researchers, and clinicians in selecting the most appropriate accelerometer specification for their investigations.
Therefore, the aim of the present study was to investigate the influence of the accelerometer OR on running parameters when reducing the OR stepwise from ±70 g to ±8 g. We hypothesized that the rapid and short spikes at the beginning of ground contact and the high accelerations during the swing phase influenced the accuracy of strLen (H1), runVel (H2), and PTA (H3) significantly, depending on the footwear conditions. The running parameters were determined based on previously published methods, and accelerometers with a high OR of ±70 g were used as the reference.
The aim of the present study was to investigate the influence of the accelerometer OR on stride length, running velocity, and on peak tibial acceleration when reducing the OR stepwise from ±70 g to ±32, ±16, and ±8 g. Biomechanical parameters were determined based on previously published methods, and accelerometers (attached at the heel cup and at the tibia) with a high OR of ±70 g were used as the reference.
The results of this study revealed that OR influences the outcomes of stride length, running velocity, and peak tibial acceleration, which were not dependent on tested footwear conditions. Lower ORs were associated with an underestimation error for all biomechanical parameters, which increased with decreasing OR. These results confirm hypotheses H1 (strLen), H2 (runVel), and H3 (PTA). Our results show that a sensor OR needs to be carefully considered when interpreting biomechanical parameters of existing investigations and when planning future studies.
Using accelerometers with an OR of ±32 g resulted in small errors, on average of up to 0.14% for strLen and 0.14% for runVel (ADIDAS). However, insignificant differences and low RMSE values were found for all footwear conditions, and therefore, the observed differences can be considered irrelevant. The accelerations during running that were measured in our study did not critically exceed the ±32 g threshold. However, our results show that when the sensor OR was limited to ±16 g or ±8 g, distinctly higher differences, when compared to the reference, were found for runVel and strLen. Due to the lower vertical and horizontal forward accelerations (set to ±16 g and ±8 g when exceeding the respective thresholds), the resulting horizontal forward velocity of the shoe (v_x) was calculated inaccurately when using the numerical integration of acc_hor. Figure 5
shows v_x for one representative stride. When observing the velocity curve progression, it seems there was a drift error after the numerical integration (frame 120 to 520), which would explain the significantly lower runVel for the OR of ±16 g and ±8 g when compared to the reference. However, to eliminate any drift error and integration offset, the shoe velocity during the flat shoe phases was assumed to be temporarily equal to zero [37
]. Therefore, the velocity was reset to zero as the stride start condition and for error back-propagation with a linear drift model [32
]. As shown in Figure 5
, the horizontal forward velocity of the foot was reset to zero in both of the flat shoe phases and no additional offset was observed for these phases. We presume, therefore, that the lower velocities were the result of ORs which were too low and were not due to a drift error.
Additionally, the results show that the stiffnesses of the tested footwear conditions do not appear to noticeably influence the accuracy of runVel. Due to the high impact loads during rearfoot running, we expected that the footwear with the highest midsole stiffness in the rearfoot area (ADIDAS) would show distinctly greater differences between ±70 g and the lower ORs, than the footwear with the lowest stiffness (ASICS). However, whereas ADIDAS revealed the highest differences between the reference OR and the reduced ORs, the ASICS shoe showed higher differences between the reference OR and the reduced ORs than PUMA (medium stiffness) did. Furthermore, similar significant differences (p < 0.001) and effect sizes between the reference OR and the OR of ±16 g and ±8 g were found for all of the footwear conditions. Therefore, due to the high accelerations which occurred during the heel strike while running in footwear with differing midsole stiffnesses, sensors with an OR greater than ±32 g should be used to measure these accelerations accurately and to calculate runVel with high accuracy (errors lower than 0.14%).
Despite the different acceleration magnitudes which occurred during heel strike for the three footwear conditions, the calculated velocities (OR: ±70 g) were comparable using the measurements taken by the light barriers (3.60 ± 0.4 m/s): ADIDAS: 3.70 ± 0.3 m/s; PUMA: 3.66 ± 0.4 m/s; ASICS: 3.60 ± 0.3 m/s. Therefore, the method for calculating runVel can be used when the OR is >±32 g.
For strLen, effects due to the lower OR were also observed. StrLen was calculated between two consecutive flat shoe phases using the integrated data from v_x. As expected, lower velocities for the reduced ORs also resulted in shorter strLen. The values of MD_rel and the significant differences between the reference and the reduced ORs, including effect sizes, were similar for strLen and runVel. This is the result of the numerical integration of v_x between two consecutive flat shoe phases when calculating strLen. Additionally, tested footwear conditions did not influence strLen calculations when using an OR of ±32 g. It seems that the critical accelerations in anterior–posterior and in vertical directions do not critically exceed the OR of ±32 g during heel strike, regardless of the midsole stiffness. However, using an OR of ±16 g can lead to strLen differences of 3.49% (MD: 9.43 cm) for each stride when running in the ADIDAS shoe. In contrast, when running in the PUMA shoe, differences of only 0.99% (MD: 2.62 cm) were found. With a further decrease in the OR, the differences between the calculated strLen of PUMA and of ADIDAS increased. When investigating mechanical midsole characteristics of footwear in biomechanical tests (e.g., benchmark tests) using an OR that is too low (<±32 g), errors in the strLen calculation can lead to incorrect conclusions. Therefore, to avoid effects of an OR that is too low, an OR of at least ±32 g should be used to measure strLen as accurately as possible and independently from the midsole stiffness of footwear.
For PTA, none of the subjects in this study generated higher peak tibial accelerations than ±32 g when running in the three provided footwear conditions (MD_rel: 0.0%; RMSE: 0.0 g). However, faster running velocities (e.g., sprint runs), running in shoes with a higher midsole stiffness (e.g., barefoot or minimal shoes), or running barefoot may increase peak tibial acceleration [10
]. In some cases, accelerations could then exceed 32 g and may lead to inaccurate results when measuring with an OR that is too low. Our results for PTA show that accuracy decreased up to 28.17% (ADIDAS: ±8 g) with lower OR. Thereby, we found that a higher midsole stiffness generally decreased the accuracy of PTA. The footwear condition with the stiffest midsole (ADIDAS) showed the greatest PTA for the reference OR (mean ± SD: 9.41 ± 5.3 g), whereas the footwear with the softest midsole configuration (ASICS) showed the lowest PTA (mean ± SD: 6.28 ± 3.0 g). When observing the mean values of PTA for each footwear condition, the minimum OR can be derived from these results.
To accurately determine PTA, a distinctly lower OR (≥±16 g) can be used in contrast to the strLen and runVel (≥±32 g). Due to various influencing factors (e.g., heel fat pad cushioning, foot pronation, shoe midsole deformation, skin displacement, and sensor wobbling), measured accelerations at the tibia were damped and were attenuated in contrast to the wobble-free sensor at the heel cup. Therefore, a distinctly lower OR is necessary for the accelerometer placed at the tibia to determine PTA without a significant loss of information. However, different locations of the accelerometers on the tibia can also influence the temporal and spectral parameters of PTA. Lucas-Cuevas et al. [45
] found that a distally placed accelerometer measured a greater PTA and shock attenuation compared to a proximal accelerometer. In our study, the accelerometer was placed at the medial aspect mid-distance between the malleolus and plateau of the right tibia according to Henning et al. [35
] and Milani et al. [12
]. Therefore, a more distal sensor attachment may require a greater OR than was recommended in our study.