Estimating effective contact and flight times using a sacral-mounted inertial measurement unit

Patoz, Aurélien; Lussiana, Thibault; Breine, Bastiaan; Gindre, Cyrille; Malatesta, Davide

doi:10.1016/j.jbiomech.2021.110667

Cited by 2 publications

(13 citation statements)

References 23 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The experimental procedure and data collection has already been described elsewhere [ 39 ]. Briefly, an IMU of 9.4 g (Movesense sensor, Suunto, Vantaa, Finland) was firmly attached to the sacrum of participants using an elastic strap belt (Movesense, Suunto, Vantaa, Finland; see first figure in [ 39 ]).…”

Section: Methodsmentioning

confidence: 99%

“…

and

are calculated from foot-strike (FS) and toe-off (TO) events, which can themselves be identified using different available techniques that used IMU data [ 24 , 25 , 29 , 30 , 31 , 32 , 33 , 34 , 35 , 36 , 37 , 38 , 39 ]. When using a sacral-mounted IMU, which is a natural choice as it approximates the location of the center of mass [ 40 ], either the forward [ 31 ] or the vertical acceleration [ 24 , 25 ] were used to estimate

and

.…”

Section: Introductionmentioning

confidence: 99%

“…A 5 Hz low-pass Butterworth filter (8th order) was shown to result in the best correlation between

, obtained from GSM and IMU data (sampled at 500 Hz) [ 24 ], while a machine learning algorithm that used data filtered using a 10 Hz 8th order low-pass Butterworth filter, resulted in an RMSE of 11 ms for

[ 25 ]. The vertical acceleration (sampled at 208 Hz) was also used to estimate the effective contact and flight times [ 39 ], two variables that allow deciphering the landing-take-off asymmetry of running [ 41 , 42 , 43 ]. The authors estimated these effective timings by using a body weight threshold instead of a 0 N threshold, which allowed detecting effective FS and TO events and thus estimating effective contact and flight times.…”

Section: Introductionmentioning

confidence: 99%

“…The second aim of this study was to estimate

and

using the same filtered acceleration signal. We previously used this filter to estimate both effective contact and flight times [ 39 ], but this filter has never been used, to the best of the authors knowledge, to estimate

, and

. In the present study,

and

were estimated from FS and TO events, themselves detected by modifying the body weight threshold we previously used [ 39 ].…”

Section: Introductionmentioning

confidence: 99%

“…We previously used this filter to estimate both effective contact and flight times [ 39 ], but this filter has never been used, to the best of the authors knowledge, to estimate

, and

. In the present study,

and

were estimated from FS and TO events, themselves detected by modifying the body weight threshold we previously used [ 39 ]. We hypothesized that (i) an RMSE smaller than or equal to the 0.15 BW reported in Alcantara, Day, Hahn and Grabowski [ 25 ] should be obtained for

, even if the IMUM is a simple method which does not rely on machine learning, as was the 3D kinematic method [ 26 ], and (ii)

and

should have an RMSE smaller than or equal to that we previously reported for effective contact and flight times (i.e., 0.22 ms) [ 39 ].…”

Section: Introductionmentioning

confidence: 99%

See 4 more Smart Citations

A Single Sacral-Mounted Inertial Measurement Unit to Estimate Peak Vertical Ground Reaction Force, Contact Time, and Flight Time in Running

Patoz

Lussiana

Breine

et al. 2022

Sensors

Self Cite

View full text Add to dashboard Cite

Peak vertical ground reaction force (Fz,max), contact time (tc), and flight time (tf) are key variables of running biomechanics. The gold standard method (GSM) to measure these variables is a force plate. However, a force plate is not always at hand and not very portable overground. In such situation, the vertical acceleration signal recorded by an inertial measurement unit (IMU) might be used to estimate Fz,max, tc, and tf. Hence, the first purpose of this study was to propose a method that used data recorded by a single sacral-mounted IMU (IMU method: IMUM) to estimate Fz,max. The second aim of this study was to estimate tc and tf using the same IMU data. The vertical acceleration threshold of an already existing IMUM was modified to detect foot-strike and toe-off events instead of effective foot-strike and toe-off events. Thus, tc and tf estimations were obtained instead of effective contact and flight time estimations. One hundred runners ran at 9, 11, and 13 km/h. IMU data (208 Hz) and force data (200 Hz) were acquired by a sacral-mounted IMU and an instrumented treadmill, respectively. The errors obtained when comparing Fz,max, tc, and tf estimated using the IMUM to Fz,max, tc, and tf measured using the GSM were comparable to the errors obtained using previously published methods. In fact, a root mean square error (RMSE) of 0.15 BW (6%) was obtained for Fz,max while a RMSE of 20 ms was reported for both tc and tf (8% and 18%, respectively). Moreover, even though small systematic biases of 0.07 BW for Fz,max and 13 ms for tc and tf were reported, the RMSEs were smaller than the smallest real differences [Fz,max: 0.28 BW (11%), tc: 32.0 ms (13%), and tf: 32.0 ms (30%)], indicating no clinically important difference between the GSM and IMUM. Therefore, these results support the use of the IMUM to estimate Fz,max, tc, and tf for level treadmill runs at low running speeds, especially because an IMU has the advantage to be low-cost and portable and therefore seems very practical for coaches and healthcare professionals.

show abstract

Section: Methodsmentioning

confidence: 99%

“…

and

.…”

Section: Introductionmentioning

confidence: 99%

“…A 5 Hz low-pass Butterworth filter (8th order) was shown to result in the best correlation between

Section: Introductionmentioning

confidence: 99%

“…The second aim of this study was to estimate

and

, and

. In the present study,

and

were estimated from FS and TO events, themselves detected by modifying the body weight threshold we previously used [ 39 ].…”

Section: Introductionmentioning

confidence: 99%

“…We previously used this filter to estimate both effective contact and flight times [ 39 ], but this filter has never been used, to the best of the authors knowledge, to estimate

, and

. In the present study,

and

, even if the IMUM is a simple method which does not rely on machine learning, as was the 3D kinematic method [ 26 ], and (ii)

and

should have an RMSE smaller than or equal to that we previously reported for effective contact and flight times (i.e., 0.22 ms) [ 39 ].…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

A Single Sacral-Mounted Inertial Measurement Unit to Estimate Peak Vertical Ground Reaction Force, Contact Time, and Flight Time in Running

Patoz

Lussiana

Breine

et al. 2022

Sensors

Self Cite

View full text Add to dashboard Cite

show abstract

Wearables for Running Gait Analysis: A Systematic Review

et al. 2022

View full text Add to dashboard Cite

Background Running gait assessment has traditionally been performed using subjective observation or expensive laboratory-based objective technologies, such as three-dimensional motion capture or force plates. However, recent developments in wearable devices allow for continuous monitoring and analysis of running mechanics in any environment. Objective measurement of running gait is an important (clinical) tool for injury assessment and provides measures that can be used to enhance performance. Objectives We aimed to systematically review the available literature investigating how wearable technology is being used for running gait analysis in adults. Methods A systematic search of the literature was conducted in the following scientific databases: PubMed, Scopus, Web of Science and SPORTDiscus. Information was extracted from each included article regarding the type of study, participants, protocol, wearable device(s), main outcomes/measures, analysis and key findings. Results A total of 131 articles were reviewed: 56 investigated the validity of wearable technology, 22 examined the reliability and 77 focused on applied use. Most studies used inertial measurement units (n = 62) [i.e. a combination of accelerometers, gyroscopes and magnetometers in a single unit] or solely accelerometers (n = 40), with one using gyroscopes alone and 31 using pressure sensors. On average, studies used one wearable device to examine running gait. Wearable locations were distributed among the shank, shoe and waist. The mean number of participants was 26 (± 27), with an average age of 28.3 (± 7.0) years. Most studies took place indoors (n = 93), using a treadmill (n = 62), with the main aims seeking to identify running gait outcomes or investigate the effects of injury, fatigue, intrinsic factors (e.g. age, sex, morphology) or footwear on running gait outcomes. Generally, wearables were found to be valid and reliable tools for assessing running gait compared to reference standards. Conclusions This comprehensive review highlighted that most studies that have examined running gait using wearable sensors have done so with young adult recreational runners, using one inertial measurement unit sensor, with participants running on a treadmill and reporting outcomes of ground contact time, stride length, stride frequency and tibial acceleration. Future studies are required to obtain consensus regarding terminology, protocols for testing validity and the reliability of devices and suitability of gait outcomes. Clinical Trial Registration CRD42021235527.

show abstract

Estimating effective contact and flight times using a sacral-mounted inertial measurement unit

Cited by 2 publications

References 23 publications

A Single Sacral-Mounted Inertial Measurement Unit to Estimate Peak Vertical Ground Reaction Force, Contact Time, and Flight Time in Running

A Single Sacral-Mounted Inertial Measurement Unit to Estimate Peak Vertical Ground Reaction Force, Contact Time, and Flight Time in Running

Wearables for Running Gait Analysis: A Systematic Review

Contact Info

Product

Resources

About