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1.
This paper presents a novel sensor technology to deduce the dynamics of a bowling ball. The sensor, a miniature wireless inertial measurement unit (IMU), incorporates MEMS accelerometers and angular rate gyros, a microcontroller, a low power RF transceiver, and a rechargeable battery. When embedded in a bowling ball, the IMU transmits the acceleration and angular velocity data that define the dynamics of the ball starting with the bowler’s delivery and its motion in the lane. Example results from professional bowlers illustrate how this technology can be used to assess bowler skill and ball performance. For instance, the IMU accurately measures the spin dynamics of the ball which are crucial to develop the ball “hook.” An analysis of ball dynamics in the lane is distilled to a measurable “hook potential” metric for further assessing bowler skill. Finally, the sensor presented herein is believed to be the world’s smallest, wireless IMU. This highly miniaturized and wireless design will enable parallel training systems for many sports, including basketball, baseball, crew, cricket, golf, fly fishing, soccer, softball, tennis, rowing, among others.  相似文献   

2.
An inertial measurement unit (IMU) is widely considered to be an economical alternative to capture human motion in daily activities. Use of an IMU for clinical study, rehabilitation, and in the design of orthoses and prostheses has increased tremendously. However, its use in defining running gait is limited. This study presents a practical method to estimate running spatial and temporal parameters using an inertial sensor by placing it on a shoe. A combination of a zero-crossing method and thresholding is used to identify foot-strike and foot-off based on foot acceleration during running. Stride time, ground contact time and flight time can then be identified. An off-phase segmentation algorithm is applied to estimate stride length and running speed. These two parameters are commonly used to evaluate running efficiency and to differentiate elite runners. This study found that an IMU can estimate foot-strike and foot-off with average absolute time differences of 2.60–6.04 and 2.61–16.28 ms, respectively. Stride time was estimated with error between ? 4.04 and 0.33 ms. Stride length and running speed were estimated with maximum average errors of 45.97 mm and 0.41 km/h.  相似文献   

3.
We present a method for quantifying sacral kinematics during countermovement jumping (CMJ) using an inertial measurement unit (IMU). The IMU-derived sacral kinematic trajectories reproduced motion capture acceleration, velocity, and displacement to within mean (standard deviation) differences of 0.024 (0.088) m/s2, 0.023 (0.026) m/s, and 0.003 (0.032) m, respectively, across 252 jumps performed by 14 subjects. The method also quantified differences in maximum sacral displacement to within 1 % and differences in maximum propulsive velocity to within 0.7 % of motion capture estimates. This builds upon existing IMU-based methods for quantifying jump performance, which do not provide sacral kinematic trajectories. The utility of this method is demonstrated by its ability to discriminate jump performance metrics across a diverse subject population. In particular, we found that 21 participants adopted multiple strategies to maximize jump height in unloaded and loaded fresh conditions, but converged to a common strategy when jumping fatigued and under load. Changes in kinematic parameters were evident across conditions, and several changes were significantly associated with changes in jump performance (i.e., height). These parameters include changes in the depth of the countermovement, duration of the propulsive phase and maximum propulsive velocity. Collectively, these results point toward the future use of this method in naturalistic environments and for multiple objectives including biomechanical performance assessment and tracking, fatigue assessment, and jump training.  相似文献   

4.
The purpose of this research was to propose a method to acquire the three-dimensional movement of a roller skiing athlete utilizing a global positioning system (GPS), an atmospheric pressure sensor (APS), and an inertial measurement unit (IMU) to distinguish between diagonal skiing and double poling techniques. In this study, we developed a lightweight wearable sensor that was composed of a GPS, APS, and IMU. For the data collection, two national level athletes roller skied a 1700 m long course where the maximum difference in elevation was 5.3 m. The planar positions of the athletes were based on the longitudinal and latitudinal data provided by the GPS, and the altitude was calculated by the International barometric formula and Laplace transform from the APS. The longitudinal and latitudinal data acquired through GPS had errors within 2 m range at each point. The altitude of Laplace transform from the APS showed errors of less than 1 m at each point. The range of motion of pelvis from the IMU was 34.0?±?3.8° for diagonal skiing, which is wider than the 21.2?±?6.9° for double poling.  相似文献   

5.
Swing trajectory and ground reaction forces (GRF) of 30 collegiate baseball batters hitting a pitched ball were compared between a standard bat, a bat with extra weight about its barrel, and a bat with extra weight in its handle. It was hypothesised that when compared to a standard bat, only a handle-weighted bat would produce equivalent bat kinematics. It was also hypothesised that hitters would not produce equivalent GRFs for each weighted bat, but would maintain equivalent timing when compared to a standard bat. Data were collected utilising a 500 Hz motion capture system and 1,000 Hz force plate system. Data between bats were considered equivalent when the 95% confidence interval of the difference was contained entirely within ±5% of the standard bat mean value. The handle-weighted bat had equivalent kinematics, whereas the barrel-weighted bat did not. Both weighted bats had equivalent peak GRF variables. Neither weighted bat maintained equivalence in the timing of bat kinematics and some peak GRFs. The ability to maintain swing kinematics with a handle-weighted bat may have implications for swing training and warm-up. However, altered timings of kinematics and kinetics require further research to understand the implications on returning to a conventionally weighted bat.  相似文献   

6.
ABSTRACT

This study investigated whether using an inertial measurement unit (IMU) can identify different walking conditions, including level walking (LW), descent (DC) and ascent (AC) slope walking as well as downstairs (DS) and upstairs (US) walking. Thirty healthy participants performed walking under five conditions. The IMU was stabilised on the exterior of the left shoe. The data from IMU were used to establish a customised prediction model by cut point and a prediction model by using deep learning method. The accuracy of both prediction models was evaluated. The customised prediction model combining the angular velocity of dorsi–plantar flexion in the heel-strike (HS) and toe-off (TO) phases can distinctly determine real conditions during DC and AC slope, DS, and LW (accuracy: 86.7–96.7%) except for US walking (accuracy: 60.0%). The prediction model established by deep learning using the data of three-axis acceleration and three-axis gyroscopes can also distinctly identify DS, US, and LW with 90.2–90.7% accuracy and 84.8% and 82.4% accuracy for DC and AC slope walking, respectively. In conclusion, inertial measurement units can be used to identify walking patterns under different conditions such as slopes and stairs with customised prediction model and deep learning prediction model.  相似文献   

7.
Magnetic and inertial measurement units (MIMUs) may provide an accessible, three-dimensional, in-field alternative to laboratory-restricted marker-based motion capture. Existing upper limb MIMU models have predominantly been validated with low-velocity motion and their suitability for use with sport-based movements remains relatively untested. We propose a MIMU system approach to enable the estimation of anatomically meaningful and participant-specific elbow kinematics with considerations for use with cricket bowling. A novel standardised elbow reference posture of 90 degrees flexion and 0 deg pronation, and functional definition of elbow joint axes of rotation calibrated the MIMU method model before it was validated across three experiments: (1) simple elbow rotations with a mechanical linkage; (2) low-velocity elbow rotations in human participants; and (3) low-medium velocity sport-based movements in human participants. The proposed MIMU method demonstrated high elbow kinematic measurement agreement when compared with a criterion measure across all three conditions. However, during experiment 3, sensor components neared their measurement capacity and the MIMU method elbow flexion measurement variability increased. We conclude that the proposed MIMU method can estimate anatomically referenced, participant-specific joint angles, however, the hardware specifications of currently available systems may limit application in high-velocity/acceleration situations, preventing the measurement of cricket bowling in-field for now.  相似文献   

8.
The aim of this study was to validate a wearable inertial measurement unit (IMU), containing a 3D accelerometer and gyroscope, for the estimation of countermovement jump height. The absolute vertical acceleration of the IMU positioned on the back of the participant at L5 level, compensated for trunk rotations, was used to obtain jump height by applying the equation of free-fall to the motion of the IMU. The methodology was tested on 28 participants performing five countermovement jumps each. A reference value for this quantity was obtained using stereophotogrammetry (35.4 cm, s = 4.9). Jump height scores obtained using the proposed methodology (35.9 cm, s = 5.5) presented no significant difference with respect to stereophotogrammetry (P = 0.61). A low bias of 0.6 cm confirmed the accuracy of the estimate, which also showed a high (r = 0.87) and significant (P < 0.0001) correlation with reference values. Furthermore, without compensating accelerations for trunk rotation, jump height was largely underestimated (P < 0.0001) (bias: -12.7 cm) and poorly associated (r = 0.31) with stereophotogrammetry. The results of this study show that the estimation of jump height using inertial sensors leads to accurate results when the measured accelerations are corrected for trunk rotations.  相似文献   

9.
The swing speed of the bat is one of the most important factors affecting the hit-ball speed. Most field studies tend to focus on measuring ball speed, which is easier to measure and quantify than bat speed. For this reason, relatively little data exist describing bat motion in field conditions. The following describes a relatively large swing speed field study involving bats of the same model with nearly constant weight and varying inertia. The study was conducted using right-handed batters on a regulation outdoor field with a live pitcher. Swing speed was measured by tracking markers on the bat with two high-speed video cameras so that the bat markers could be traced in three-dimensional space. The ball motion was tracked using the same high-speed video cameras and a three-dimensional Doppler radar system. Bat swing speed was observed to be proportional to the batter skill level and the normalised swing speed increased with decreasing bat inertia. The bat centre of rotation during impact was close to the knob of the bat. The bats were tested under controlled laboratory conditions using a standardised performance test. The field and laboratory results showed good agreement including the hit-ball speed and the subtle effect of bat inertia on the maximum performance location. The vibrational response of the bats was considered using modal analysis. The maximum performance location was correlated with the node of the first vibrational mode.  相似文献   

10.
For a valid determination of a rower’s mechanical power output, the anterior–posterior (AP) acceleration of a rower’s centre of mass (CoM) is required. The current study was designed to evaluate the accuracy of the determination of this acceleration using a full-body inertial measurement units (IMUs) suit in combination with a mass distribution model. Three methods were evaluated. In the first two methods, IMU data were combined with either a subject-specific mass distribution or a standard mass distribution model for athletes. In the third method, a rower’s AP CoM acceleration was estimated using a single IMU placed at the pelvis.

Experienced rowers rowed on an ergometer that was placed on two force plates, while wearing a full-body IMUs suit. Correspondence values between AP CoM acceleration based on IMU data (the three methods) and AP CoM acceleration obtained from force plate data (reference) were calculated. Good correspondence was found between the reference AP CoM acceleration and the AP CoM accelerations determined using IMU data in combination with the subject-specific mass model and the standard mass model (intraclass correlation coefficients [ICC] >?0.988 and normalized root mean square errors [nRMSE]?3.81%). Correspondence was lower for the AP CoM accelerations determined using a single pelvis IMU (0.877?Based on these results, we recommend determining a rower’s AP CoM acceleration using IMUs in combination with the standard mass model. Finally, we conclude that accurate determination of a rower’s AP CoM acceleration is not possible on the basis of the pelvis acceleration only.  相似文献   

11.
This study investigated the reliability of a wireless accelerometer and its agreement with optical motion capture for the measurement of root mean square (RMS) acceleration during running. RMS acceleration provides a whole-body metric of movement mechanics and economy. Fifteen healthy college-age participants performed treadmill running for two 60-s trials at 2.22, 2.78, and 3.33 m/s and one trial of 150 s (five 30-s epochs) at 2.78 m/s. We assessed between-trial and within-trial reliability, and agreement in each axis between a trunk-mounted wireless accelerometer and a reflective marker on the accelerometer measured by optical motion capture. Intraclass correlations assessing between-trial repeatability were 0.89–0.97, depending on the axis, and intraclass correlations assessing within-trial repeatability were 0.99–1.00. Bland–Altman analyses assessing agreement indicated mean difference values between ?0.03 and 0.03 g, depending on the axis. Anterio-posterior acceleration had the greatest limits of agreement (LOA) (±0.12 g) and vertical acceleration had the smallest LOA (±0.03 g). For measuring RMS acceleration of the trunk, this wireless accelerometer node provides repeatable and valid measurement compared with the standard laboratory method of optical motion capture.  相似文献   

12.
New cricket bats need to be ‘knocked in’ prior to use, but just what this process does to the surface fibres of the bat is unknown and unquantified. One quantitative measurement of knock-in is the resultant surface hardness of the bat, and this paper describes knock-in tests to determine the surface hardness following differing durations of knock-in. The design of a cricket bat knock-in machine is first described. This takes the form of a cradle in which a cricket bat can be secured horizontally and then traversed at constant speeds in two mutually perpendicular directions while at the same time being struck with constant force by a cricket ball. The traverses are driven by lead screws, the motors of which can be independently switched on or off. The traverse distance can be varied with adjustable limit switches and relays that reverse the direction of rotation of the lead screws when activated. The cricket ball is attached to a rod that is lifted cyclically by a cam against a coil spring extension, and then allowed to fall under that force to impact on the bat surface. The impact (knocking-in) force was measured by a previously calibrated strain gauge attached to the rod holding the cricket ball. By judicious setting of the limit switches, selected areas of the bat surface were continuously knocked in for periods varying from 1 to 4 hours. After knocking in, the surface hardness was measured in accordance with British Standard 373 using a penetrator designed in accordance with the same standard. Analysis of the load/penetration curves shows an increase in surface hardness with knock duration. Photographs of the cell structure of the surface wood, obtained using a scanning electron microscope, show that under knock-in conditions, the wood cells collapse to form a mesh-like hardened layer which increases in hardness with increase in knock-in duration.  相似文献   

13.
Biomechanical analyses using synchronized tools [electromyography (EMG), motion capture, force sensors, force platform, and digital camera] are classically performed in a laboratory environment that could influence the performance. We present a system for studying the running sprint start that synchronizes motion capture, EMG, and ground reaction force data. To maximize motion capture (Vicon 612 with six cameras), a special dim environment was created in the stadium. "Classical" tools were combined with "purpose-built" tools intended to analyse the different aspects of movement. For example, a synchronization system was built to create a common time-base for all data recordings and a portable EMG system was synchronized by a cable that was "disconnected" by the athlete's movement out of the blocks. This disconnection represented an independent event recorded by different tools. A "gap" was measured for some sprint start events between kinetic and kinematic (motion capture) data. Calibration results, measurements of time "gap", and duration of the independent event were used to validate the accuracy of motion capture and the synchronization system. The results validate the entire experimental set-up and suggest adjustment values for motion capture data. This environment can be used to study other movements and can easily be applied to several sports.  相似文献   

14.
The main objective of this research was to develop a markerless optical motion capture system that can be used for daily use in swimming training. The butterfly stroke was targeted since it is considered bilaterally symmetric in motion. The system consisted of a segmentation process to obtain the participant’s silhouettes and a matching process to estimate the pose of the participant. A variable thresholding method was used to extract the silhouettes to solve non-uniform illumination in the recorded swimming video. Prior to the matching process, the human body was modeled as a series of nine segments to help the matching process. The model was then mapped so that it aligned with the silhouettes, which were investigated by similarity of intensity value. To minimize the degree of freedom in image matching, the available joint motion in the swimming human simulation model was used as a priori information for kinematics data of the swimming motion. As a result, the rotation angle’s correlation coefficients between the references and result of the matching process were around 0.95 for trunk, thigh, shank, upper arm, forearm, hand and 0.78 for head, hip and foot. The rotation angle and the velocity of the center of mass were put into the swimming human simulation model for a dynamics analysis. The simulation results show that the velocity obtained in the experiment corresponded to the fluid force exerted on the lower and upper limbs. Consequently, the proposed system of obtaining the joint motion of the butterfly stroke is suitable for daily training and coaching.  相似文献   

15.
The motion capture of alpine skiing is technically challenging. Motion capture systems using inertial sensors such as gyroscopes and accelerometers have begun to be used in sport. The capture volume of the system can be large enough to cover the whole area of a particular sporting event, because sensors are affixed to the human body itself. The current study developed a method of tracking the pose of an alpine skier using gyroscopes for 3 min with a tracking error of 2° (RMSE). The technical significance of the presented method, which uses one common simple algorithm to improve measurement of pose, applies to many experimental conditions. The adoption of a high resolution (24 bit) analog-to-digital converter and high sampling rate (1 kHz) also contribute to the improvement of measurement time.  相似文献   

16.
Objective assessment of an athlete’s performance is of importance in elite sports to facilitate detailed analysis. The implementation of automated detection and recognition of sport-specific movements overcomes the limitations associated with manual performance analysis methods. The object of this study was to systematically review the literature on machine and deep learning for sport-specific movement recognition using inertial measurement unit (IMU) and, or computer vision data inputs. A search of multiple databases was undertaken. Included studies must have investigated a sport-specific movement and analysed via machine or deep learning methods for model development. A total of 52 studies met the inclusion and exclusion criteria. Data pre-processing, processing, model development and evaluation methods varied across the studies. Model development for movement recognition were predominantly undertaken using supervised classification approaches. A kernel form of the Support Vector Machine algorithm was used in 53% of IMU and 50% of vision-based studies. Twelve studies used a deep learning method as a form of Convolutional Neural Network algorithm and one study also adopted a Long Short Term Memory architecture in their model. The adaptation of experimental set-up, data pre-processing, and model development methods are best considered in relation to the characteristics of the targeted sports movement(s).  相似文献   

17.
目的:将惯性陀螺方法和基于标志点虚拟陀螺(a Marker-Based Virtual Gyroscope简称MBVG)方法用于网球发球时上臂内转动动作的监测,并对监测结果同视频拍摄方法研究结果进行比较。方法:惯性陀螺方法利用上臂和胸部两个陀螺对网球发球中上臂的转动进行捕捉。MBVG方法根据Vicon光学动作捕捉系统来设置标志点,利用标志点轨迹建立一种基于向量的方法,并利用几何方法确定转动关系。结果:(1)惯性陀螺方法与视频拍摄方法的结果在规范化时间的0.2~1区间段一致性很好,表明此方法在测量上臂内转动上是有效的;(2)MBVG方法能够用于陀螺超量程的情况,其数据能够反映真实的发球动作;(3)3种方法测得的网球发球数据在特征上彼此能够很好的吻合。结论:惯性陀螺方法与基于标志点虚拟陀螺方法能够有效地用于网球发球评估。  相似文献   

18.
ABSTRACT

The study purpose was to use Inertial Measurement Units (IMUs) to objectively assess children’s motor competence in seven movement skills. Fourteen children aged from seven to 12 years (M = 9.64) participated. Children were asked to perform up to 10 trials of each skill. Children performed the skills, which were captured by XSENS MVN Awinda wireless motion capture, and video. Skills were assessed from video as per the criteria from the Test of Gross Motor Development 3. Initially, 17 IMU sensors were used for signal processing, but this was restricted to four sensors (wrists and ankles) to be more feasible for field assessment. Results of the signal testing against its modelled “Good” signal, showed the skip was classified correctly each time, as was the sidestep. Accuracy % rates for each skill were: kick (95.2), catch (95.0), throw (80.5), jump (78.9), and hop (76.9). Using signal processing-based methods via four sensors was a reliable and feasible way to assess seven motor skills in children. This approach means monitoring and assessment of children’s skills can be objective, which will potentially reduce the time involved in motor skill assessment and analysis for research, clinical, sport and education purposes.  相似文献   

19.
Objective: Sport research often requires human motion capture of an athlete. It can, however, be labour-intensive and difficult to select the right system, while manufacturers report on specifications which are determined in set-ups that largely differ from sport research in terms of volume, environment and motion. The aim of this review is to assist researchers in the selection of a suitable motion capture system for their experimental set-up for sport applications. An open online platform is initiated, to support (sport)researchers in the selection of a system and to enable them to contribute and update the overview. Design: systematic review; Method: Electronic searches in Scopus, Web of Science and Google Scholar were performed, and the reference lists of the screened articles were scrutinised to determine human motion capture systems used in academically published studies on sport analysis. Results: An overview of 17 human motion capture systems is provided, reporting the general specifications given by the manufacturer (weight and size of the sensors, maximum capture volume, environmental feasibilities), and calibration specifications as determined in peer-reviewed studies. The accuracy of each system is plotted against the measurement range. Conclusion: The overview and chart can assist researchers in the selection of a suitable measurement system. To increase the robustness of the database and to keep up with technological developments, we encourage researchers to perform an accuracy test prior to their experiment and to add to the chart and the system overview (online, open access).  相似文献   

20.
In this paper a video-based method to automatically track instantaneous velocities of a swimmer is presented. Single cameras were used to follow a marker (LED) attached to the body. The method is inspired by particle tracking techniques, traditionally used in the field of fluid dynamics, to measure local velocities of a fluid flow. During the validation experiment, a white LED was attached to the hip of a swimmer together with a speedometer. A swimmer performed four different stroke types. The velocity profiles using LED tracking were captured and showed less noise than the speedometer measurements. Only at times when the marker disappeared above the water surface due to body role in front crawl and backstroke swimming did the LED tracking fail to capture the athlete’s motion. The algorithm was tested in a 2D case with a single LED to illustrate the proof of principle, but should be suitable for implementation in a 3D analysis or multiple LED analysis.  相似文献   

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