Literature DB >> 29920155

Running patterns for male and female competitive and recreational runners based on accelerometer data.

Christian A Clermont1, Lauren C Benson1, Sean T Osis1,2, Dylan Kobsar1, Reed Ferber1,2,3.   

Abstract

The purpose of this study was to classify runners in sex-specific groups as either competitive or recreational based on center of mass (CoM) accelerations. Forty-one runners participated in the study (25 male and 16 female), and were labeled as competitive or recreational based on age, sex, and race performance. Three-dimensional acceleration data were collected during a 5-minute treadmill run, and 24 features were extracted. Support vector machine classification models were used to examine the utility of the features in discriminating between competitive and recreational runners within each sex-specific subgroup. Competitive and recreational runners could be classified with 82.63 % and 80.4 % in the male and female models, respectively. Dominant features in both models were related to regularity and variability, with competitive runners exhibiting more consistent running gait patterns, but the specific features were slightly different in each sex-specific model. Therefore, it is important to separate runners into sex-specific competitive and recreational subgroups for future running biomechanical studies. In conclusion, we have demonstrated the ability to analyze running biomechanics in competitive and recreational runners using only CoM acceleration patterns. A runner, clinician, or coach may use this information to monitor how running patterns change as a result of training.

Keywords:  Running biomechanics; accelerometer; gait analysis

Mesh:

Year:  2018        PMID: 29920155     DOI: 10.1080/02640414.2018.1488518

Source DB:  PubMed          Journal:  J Sports Sci        ISSN: 0264-0414            Impact factor:   3.337


  14 in total

1.  Wearables for Running Gait Analysis: A Systematic Review.

Authors:  Rachel Mason; Liam T Pearson; Gillian Barry; Fraser Young; Oisin Lennon; Alan Godfrey; Samuel Stuart
Journal:  Sports Med       Date:  2022-10-15       Impact factor: 11.928

2.  Recent Machine Learning Progress in Lower Limb Running Biomechanics With Wearable Technology: A Systematic Review.

Authors:  Liangliang Xiang; Alan Wang; Yaodong Gu; Liang Zhao; Vickie Shim; Justin Fernandez
Journal:  Front Neurorobot       Date:  2022-06-02       Impact factor: 3.493

3.  Lower limb joint motion and muscle force in treadmill and over-ground exercise.

Authors:  Jie Yao; Ning Guo; Yanqiu Xiao; Zhili Li; Yinghui Li; Fang Pu; Yubo Fan
Journal:  Biomed Eng Online       Date:  2019-08-22       Impact factor: 2.819

4.  The kinematics of cyclic human movement.

Authors:  Manfred M Vieten; Christian Weich
Journal:  PLoS One       Date:  2020-03-05       Impact factor: 3.240

5.  Using Artificial Intelligence for Pattern Recognition in a Sports Context.

Authors:  Ana Cristina Nunes Rodrigues; Alexandre Santos Pereira; Rui Manuel Sousa Mendes; André Gonçalves Araújo; Micael Santos Couceiro; António José Figueiredo
Journal:  Sensors (Basel)       Date:  2020-05-27       Impact factor: 3.576

6.  The Relationship between VO2max, Power Management, and Increased Running Speed: Towards Gait Pattern Recognition through Clustering Analysis.

Authors:  Juan Pardo Albiach; Melanie Mir-Jimenez; Vanessa Hueso Moreno; Iván Nácher Moltó; Javier Martínez-Gramage
Journal:  Sensors (Basel)       Date:  2021-04-01       Impact factor: 3.576

7.  Principal Component Analysis of the Running Ground Reaction Forces With Different Speeds.

Authors:  Lin Yu; Qichang Mei; Liangliang Xiang; Wei Liu; Nur Ikhwan Mohamad; Bíró István; Justin Fernandez; Yaodong Gu
Journal:  Front Bioeng Biotechnol       Date:  2021-03-25

8.  Track distance runners exhibit bilateral differences in the plantar fascia stiffness.

Authors:  Hiroto Shiotani; Ryo Yamashita; Tomohiro Mizokuchi; Natsuki Sado; Munekazu Naito; Yasuo Kawakami
Journal:  Sci Rep       Date:  2021-04-29       Impact factor: 4.379

9.  Evaluation of COVID-19 Restrictions on Distance Runners' Training Habits Using Wearable Trackers.

Authors:  Zoe Y S Chan; Rhys Peeters; Gladys Cheing; Reed Ferber; Roy T H Cheung
Journal:  Front Sports Act Living       Date:  2022-01-12

Review 10.  Is This the Real Life, or Is This Just Laboratory? A Scoping Review of IMU-Based Running Gait Analysis.

Authors:  Lauren C Benson; Anu M Räisänen; Christian A Clermont; Reed Ferber
Journal:  Sensors (Basel)       Date:  2022-02-23       Impact factor: 3.576

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