Dataset Information

Stride and Step Length Obtained with Inertial Measurement Units during Maximal Sprint Acceleration.

ABSTRACT: During sprint acceleration, step length, step rate, ground contact, and airtime are key variables for coaches to guide the training process and technical development of their athletes. In the field, three of these variables are easily obtained with inertial measurement units (IMUs), but, unfortunately, valid estimates of step length with IMUs currently are limited to low speeds (<50% max). A simple method is proposed here to derive step length during maximal sprint acceleration, using IMUs on both feet and two timing gates only. Mono-exponential velocity-time functions are fitted to the 30-m (split) and 60-m times, which in combination with IMU-derived step durations yield estimates of step length. To validate this approach, sixteen well-trained athletes with IMUs on the insteps of both feet executed two 60-m maximal sprints, starting from a three-point position. As a reference, step lengths were determined from video data. The reference step lengths combined with IMU-derived step durations yielded a time series of step velocity that confirmed the appropriateness of a mono-exponential increase of step velocity (R2 ? 0.96). The comparison of estimated step lengths to reference measurements showed no significant difference (p > 0.05) and acceptable agreement (root mean square error, RMSE = 8.0 cm, bias ± Limits of Agreement = -0.15 ± 16 cm). Step length estimations further improved (RMSE = 5.7 cm, -0.16 ± 11 cm) after smoothing the original estimated step lengths with a third order polynomial function (R2 = 0.94 ± 0.04). In conclusion, during maximal sprint acceleration, acceptable estimates of stride and step length were obtained from IMU-derived step times and 30-m (split) and 60-m sprint times.

SUBMITTER: de Ruiter CJ

PROVIDER: S-EPMC6784208 | biostudies-literature | 2019 Aug

REPOSITORIES: biostudies-literature

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Stride and Step Length Obtained with Inertial Measurement Units during Maximal Sprint Acceleration.

de Ruiter Cornelis J CJ van Dieën Jaap H JH

Sports (Basel, Switzerland) 20190831 9

During sprint acceleration, step length, step rate, ground contact, and airtime are key variables for coaches to guide the training process and technical development of their athletes. In the field, three of these variables are easily obtained with inertial measurement units (IMUs), but, unfortunately, valid estimates of step length with IMUs currently are limited to low speeds (<50% max). A simple method is proposed here to derive step length during maximal sprint acceleration, using IMUs on bo ...[more]

PMID: 31480457

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Project description:Background: Objective gait assessment is key for the follow-up of patients with progressive multiple sclerosis (pMS). Inertial measurement units (IMUs) provide reliable and yet easy quantitative gait assessment in routine clinical settings. However, to the best of our knowledge, no automated step-detection algorithm performs well in detecting severely altered pMS gait. Method: This article elaborates on a step-detection method based on personalized templates tested against a gold standard. Twenty-two individuals with pMS and 10 young healthy subjects (HSs) were instructed to walk on an electronic walkway wearing synchronized IMUs. Templates were derived from the IMU signals by using Initial and Final Contact times given by the walkway. These were used to detect steps from other gait trials of the same individual (intra-individual template-based detection, IITD) or another participant from the same group (pMS or HS) (intra-group template-based detection, IGTD). All participants were seen twice with a 6-month interval, with two measurements performed at each visit. Performance and accuracy metrics were computed, along with a similarity index (SId), which was computed as the mean distance between detected steps and their respective closest template. Results: For HS participants, both the IITD and the IGTD algorithms had precision and recall of 1.00 for detecting steps. For pMS participants, precision and recall ranged from 0.94 to 1.00 for IITD and 0.85 to 0.95 for IGTD depending on the level of disability. The SId was correlated with performance and the accuracy of the result. An SId threshold of 0.957 (IITD) and 0.963 (IGTD) could rule out decreased performance (F-measure ? 0.95), with negative predictive values of 0.99 and 0.96 with the IITD and IGTD algorithms. Also, the SId computed with the IITD and IGTD algorithms could distinguish individuals showing changes at 6-month follow-up. Conclusion: This personalized step-detection method has high performance for detecting steps in pMS individuals with severely altered gait. The algorithm can be self-evaluating with the SI, which gives a measure of the confidence the clinician can have in the detection. What is more, the SId can be used as a biomarker of change in disease severity occurring between the two measurement times.

Project description:BackgroundWalking patterns can provide important indications of a person's health status and be beneficial in the early diagnosis of individuals with a potential walking disorder. For appropriate gait analysis, it is critical that natural functional walking characteristics are captured, rather than those experienced in artificial or observed settings. To better understand the extent to which setting influences gait patterns, and particularly whether observation plays a varying role on subjects of different ages, the current study investigates to what extent people walk differently in lab versus real-world environments and whether age dependencies exist.MethodsThe walking patterns of 20 young and 20 elderly healthy subjects were recorded with five wearable inertial measurement units (ZurichMOVE sensors) attached to both ankles, both wrists and the chest. An automated detection process based on dynamic time warping was developed to efficiently identify the relevant sequences. From the ZurichMOVE recordings, 15 spatio-temporal gait parameters were extracted, analyzed and compared between motion patterns captured in a controlled lab environment (10 m walking test) and the non-controlled ecologically valid real-world environment (72 h recording) in both groups.ResultsSeveral parameters (Cluster A) showed significant differences between the two environments for both groups, including an increased outward foot rotation, step width, number of steps per 180° turn, stance to swing ratio, and cycle time deviation in the real-world. A number of parameters (Cluster B) showed only significant differences between the two environments for elderly subjects, including a decreased gait velocity (p = 0.0072), decreased cadence (p = 0.0051) and increased cycle time (p = 0.0051) in real-world settings. Importantly, the real-world environment increased the differences in several parameters between the young and elderly groups.ConclusionElderly test subjects walked differently in controlled lab settings compared to their real-world environments, which indicates the need to better understand natural walking patterns under ecologically valid conditions before clinically relevant conclusions can be drawn on a subject's functional status. Moreover, the greater inter-group differences in real-world environments seem promising regarding the sensitive identification of subjects with indications of a walking disorder.

Project description:Objectives The purpose of this study is to determine the associations between horizontal jump and sprint acceleration, as well as maximal speed performance. Methods A systematic literature search was performed using PubMed, MEDLINE (EBSCOhost), and Web of Science. The studies that were included in this review must meet the following criteria: (1) well-trained individuals over the age of 18 years old; (2) Pearson’s correlation coefficients between sprint time and horizontal jump distance were provided; (3) the sprint distance was limited to 0–100 m. The quality of the studies was assessed using a modified version of the Downs and Black Quality Index test. A random-effects model was used to determine the effect sizes, and heterogeneity between studies was examined using the Q statistic and I2. Results From the identified 2,815 studies, 27 studies were included in this study (two from reference lists). The sprint time of the sprint acceleration phase was moderately and negatively correlated with the standing long jump (r = − 0.45, z = 7.48, p < 0.001), single leg standing long jump (r = − 0.48, z = 3.49, p < 0.001) and horizontal drop jump distance (r = − 0.48, z = 3.49, p < 0.001), and was largely and negatively correlated with multiple jump distance (r = − 0.69, z = 6.02, p < 0.001). Out of five studies assessed the standing triple jump, three studies reported significant positive association with the sprint acceleration performance. The sprint time of maximal speed phase was very largely and negatively associated with standing long jump distance (r = − 0.73, z = 4.44, p < 0.001) and multiple jump distance (r = − 0.76, z = 6.86, p < 0.001). Conclusions This review indicates the moderate to very large associations between horizontal jump and sprint acceleration and maximal speed performance, and the highest magnitude of associations between them is found in the multiple jump. Moreover, compared to the sprint acceleration performance, there are greater associations between maximal speed performance and standing long jump and multiple jump distance.

Dataset Information

Stride and Step Length Obtained with Inertial Measurement Units during Maximal Sprint Acceleration.

Publications

Stride and Step Length Obtained with Inertial Measurement Units during Maximal Sprint Acceleration.

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