Detecting and Sonifying Temporal Patterns of Body Segments When Batting

Similar documents
Utilizing Virtual Reality to Understand Athletic Performance and Underlying Sensorimotor Processing

Impact Points and Their Effect on Trajectory in Soccer

Kinematic Differences between Set- and Jump-Shot Motions in Basketball

Effect of the Grip Angle on Off-Spin Bowling Performance Parameters, Analysed with a Smart Cricket Ball

Variable Face Milling to Normalize Putter Ball Speed and Maximize Forgiveness

Shoe-shaped Interface for Inducing a Walking Cycle

Development of a Simulation Model for Swimming with Diving Fins

A Feedback System for the Motor Learning of Skills in Golf

Effect on Bowling Performance Parameters When Intentionally Increasing the Spin Rate, Analysed with a Smart Cricket Ball

+ t1 t2 moment-time curves

The Estimation Of Compressor Performance Using A Theoretical Analysis Of The Gas Flow Through the Muffler Combined With Valve Motion

Analysis of Swing Movement in Ballroom Dancing

Comparison of Active Drag Using the MRT-Method and the MAD-System in Front Crawl Swimming

Procedia Engineering Procedia Engineering 2 (2010)

Simulation analysis of the influence of breathing on the performance in breaststroke

Towards determining absolute velocity of freestyle swimming using 3-axis accelerometers

Dynamic analysis and motion measurement of ski turns using inertial and force sensors

Available online at Procedia Engineering 200 (2010) (2009) In situ drag measurements of sports balls

Accelerometers: An Underutilized Resource in Sports Monitoring

INTERACTION OF STEP LENGTH AND STEP RATE DURING SPRINT RUNNING

TEMPORAL STRUCTURE OF A LEFT HAND TOSS VS. A RIGHT-HAND TOSS OF THE VOLLEYBALL JUMP SERVE

Friction properties of the face of a hand-held tennis racket

Sinusoidal Waves. Sinusoidal Waves. Sinusoidal Waves

Experiment of a new style oscillating water column device of wave energy converter

Supplementary materials

A QUALITATIVE ANALYSIS OF THE HIGH RACQUET POSITION BACKHAND DRIVE OF AN ELITE RACQUETBALL PLAYER

SIMULTANEOUS RECORDINGS OF VELOCITY AND VIDEO DURING SWIMMING

Available online at ScienceDirect. Procedia Engineering 112 (2015 )

Aerodynamic characteristics around the stalling angle of the discus using a PIV

ScienceDirect. Rebounding strategies in basketball

KASAMATSU VERSUS TSUKAHARA VAULT

Analysis of Backward Falls Caused by Accelerated Floor Movements Using a Dummy

Optimal Football Pressure as a Function of a Footballer s Physical Abilities

G.C.E (A/L) Examination March In collaboration with

APPLICATION OF THREE DIMENSIONAL ACCELEROMETRY TO HUMAN MOTION ANALYSIS

Datalogging Shirt for Baseball Pitchers

Harmonics and Sound Exam Review

Available online at ScienceDirect. Procedia Engineering 112 (2015 )

Aerodynamic behavior of a discus

Anatomy of a Homer. Purpose. Required Equipment/Supplies. Optional Equipment/Supplies. Discussion

Chapter 11 Waves. Waves transport energy without transporting matter. The intensity is the average power per unit area. It is measured in W/m 2.

Designing Wave Energy Converting Device. Jaimie Minseo Lee. The Academy of Science and Technology The Woodlands College Park High School, Texas

Available online at Procedia Engineering 00 (2011) Field Measurements of Softball Player Swing Speed

Lesson 14: Simple harmonic motion, Waves (Sections )

Mutual and asynchronous anticipation and action in sports as globally competitive

Analysis of stroke technique using acceleration sensor IC in freestyle swimming

EXPERIMENTAL STUDY ON THE HYDRODYNAMIC BEHAVIORS OF TWO CONCENTRIC CYLINDERS

Add this important safety precaution to your normal laboratory procedures:

Development of a New Performance Metric for Golf Clubs Using COR Maps and Impact Probability Data

Variation of Nordic Classic Ski Characteristics from Norwegian national team athletes

Lesson 3. Golf. Lesson Objectives. Personal Conditioning. Prepare Students... 3 min Explain/Demonstrate/Practice

Common Hitting Faults

BROCK UNIVERSITY. Name: Student #: Page 1 of 12

Walking with coffee: when and why coffee spills

The effects of a suspended-load backpack on gait

Figure 8.45 (continued) Hit easy grounders directly to the players.

Ball impact dynamics of knuckling shot in soccer

Physics Wave Problems. Science and Mathematics Education Research Group

Hunting for the Sweet Spot by a Seesaw Model

ITF Coaches Education Programme Biomechanics of the forehand stroke

APPROACH RUN VELOCITIES OF FEMALE POLE VAULTERS

Agood tennis player knows instinctively how hard to hit a ball and at what angle to get the ball over the. Ball Trajectories

Artifacts Due to Filtering Mismatch in Drop Landing Moment Data

An investigation of kinematic and kinetic variables for the description of prosthetic gait using the ENOCH system

TRIAXYS Acoustic Doppler Current Profiler Comparison Study

by Michael Young Human Performance Consulting

Influence of Toe-Hang vs. Face-Balanced Putter Design on Golfer Applied Kinetics

Flight Corridor. The speed-altitude band where flight sustained by aerodynamic forces is technically possible is called the flight corridor.

AN31E Application Note

ABCA Research Committee

A portable roller ski rolling resistance measurement system

t h e g o l f r o b ot 3.0 t r a i n i n g sy st e m m a d e i n g e r m a n y

Available online at ScienceDirect. Procedia Engineering 112 (2015 )

PROPER PITCHING MECHANICS

Predicting Ground Reaction Forces in Sprint Running Using a Shank Mounted Inertial Measurement Unit

ScienceDirect. Relating baseball seam height to carry distance

Smart Water Application Technologies (SWAT)

FORM WITHOUT FEAR Groundstrokes and Footwork

Measuring Sound Speed in Gas Mixtures Using a Photoacoustic Generator

Innovative Golf Putter

Body Stabilization of PDW toward Humanoid Walking

AN EXPERIMENTAL INVESTIGATION OF SPILLING BREAKERS

Chapter 15 Wave Motion. Copyright 2009 Pearson Education, Inc.

LABORATORY EXPERIMENTS ON WAVE OVERTOPPING OVER SMOOTH AND STEPPED GENTLE SLOPE SEAWALLS

QUICK TIPS THROWING & FIELDING

Kobe University Repository : Kernel

Open Research Online The Open University s repository of research publications and other research outputs

Video Based Accurate Step Counting for Treadmills

Characteristics of modern soccer balls

Preview. Vibrations and Waves Section 1. Section 1 Simple Harmonic Motion. Section 2 Measuring Simple Harmonic Motion. Section 3 Properties of Waves

6 Motion in Two Dimensions BIGIDEA Write the Big Idea for this chapter.

Procedia Engineering 00 2 (2010) (2009) Properties of friction during the impact between tennis racket surface and ball

EMPIRICAL FORMULA OF DISPERSION RELATION OF WAVES IN SEA ICE

sensors ISSN

Using an Adaptive Thresholding Algorithm to Detect CA1 Hippocampal Sharp Wave Ripples. Jay Patel. Michigan State University

Sound waves... light waves... water waves...

EXPERIMENTAL RESULTS OF GUIDED WAVE TRAVEL TIME TOMOGRAPHY

AN ISOLATED SMALL WIND TURBINE EMULATOR

Transcription:

Proceedings Detecting and Sonifying Temporal Patterns of Body Segments When Batting Akemi Kobayashi, *, Daiki Nasu, Yota Morimoto 3, Makio Kashino and Toshitaka Kimura NTT Service Evolution Laboratories, -, Hikarinooka, Yokosuka, Kanagawa 38-87, Japan NTT Communication Science Laboratories, 3-, Wakamiya, Morinosato, Atsugi 3-98, Japan; nasu.daiki@lab.ntt.co.jp (D.N.); kashino.makio@lab.ntt.co.jp (M.K.); kimura.toshitaka@lab.ntt.co.jp (T.K.) 3 MDOOS, Bezuidenhoutseweg -, 9AC The Hague, The Netherlands; yotamorimoto@gmail.com * Correspondence: kobayashi.akemi@lab.ntt.co.jp; Tel.: +8--89-78 Presented at the th Conference of the International Sports Engineering Association, Brisbane, Queensland, Australia, 9 March 8. Published: February 8 Abstract: To improve skill in sport activities it is essential to discern the temporal patterns of one s own movements. Our previous motion capture experiment involving elite female softball players identified key differences in the temporal body movements between the top players and young players against fastballs/change-ups. In this paper, we found that key features could be extracted from the rotation of the pelvis and we developed a sonification feedback system with two nine-axes inertial sensors. Rotation patterns are converted into two synthesized sounds to represent the time at peak trunk rotation speed and impact time. We conducted a pilot experiment with this feedback proposal using expert and novice batters, male and female whether the participants can pace of the rotational motion in batting. As a result, this feedback approach may allow the user to alter the time of peak trunk rotation speed to more closely match the cue provided by the training sound. Keywords: softball; trunk motion; feedback; sonification. Introduction Skillful sports actions such as baseball batting, softball batting and golf shots depend on temporal coordination of body segments in extremely short periods. To develop a skillful batting technique for baseball and softball demands compound movements that can respond to deliveries with various speeds and trajectories. In order to produce high bat speeds and power, it is necessary for the body segments to accelerate at the proper timing []. It is essential to understand the temporal patterns of one s own movements if we are to improve our sports skill. Complicated sensing systems may have high accuracy and full body coverage but they preclude daily practice that is essential to develop dependable skills. For daily use, a simple measuring system is useful. However, developing a feedback system for quick movement patterns is not easy. It is important to consider what kind of modality should be used for feedback of the motion. Visual feedback has insufficient temporal resolution and can be distracting. Auditory feedback is the more attractive candidate because auditory perception has high temporal resolution []. For cycling, auditory feedback was used to visualize motion [3]. We considered that auditory feedback can reflect time structure well and focused on auditory feedback. The purpose of this study is to develop a batting motion system that can easily assess and improve the fundamental body movements by extracting and sonifying the fundamental metrics of whole body motion pattern. Proceedings 8, ; doi:.339/proceedings www.mdpi.com/journal/proceedings

Proceedings 8,, of. Materials and Methods.. Detecting Essential Features of Batting In baseball and softball, a good batter adjusts his/her body motion to the wide range of ball speeds and trajectories expected. Our previous experiment with elite female softball players, some of whom had been on the national team, evaluated the movement features that occur during batting as regards two types of pitching (fastball and change-up), with different ball speeds (approximately 9 and 7 km/h, respectively) []. The participants were asked to hit randomly pitched fastballs and change-ups. For each of the first three fastballs and three change-ups, the batters were informed of the type of pitch that would be thrown (known condition), and thereafter they were not informed ( condition). The whole body movements of both the batter and pitcher were recorded simultaneously by a motion capture system ( Hz, MVN BIOMECH Link, Xsense Inc, Enschede, The Netherlands). All procedures used in this research were approved by the research ethics committee of NTT Communication Science Laboratories. It was shown that superior batters could adjust the timing of their swing motion to the ball impact according to pitch type with a high degree of accuracy. With a change-up, they paused their swing motion by about 3 ms after the ball was released and then continued their swing, which was not the case with young batters as shown as Figure. Figure. The top two figures show the relative velocity of each body segment and the bottom show the sum of whole body velocities. Extracting Essential Features We conducted further analysis based on this experimental data and we found that key features were extracted from the rotation of the pelvis. Figure shows plots of the squared sum of angular velocity components of pelvis. The motion pattern described in Figure that pausing the swing motion after about 3 ms after the change-up ball was released and continuing the swing was seen in the movement of the pelvis rotation. angular velocity (squared sum) [rad/sec].. Time [s]..8.. Time [s]..8 time from ball release [s] time from ball release [s] Figure. Trajectories of the squared sum of angular velocity components of pelvis (left: top batter (), right: young batter ().

Proceedings 8,, 3 of Figure 3a shows plots of the squared sum of angular velocity components of pelvis aligned at impact time. A superior batter could reproduce their pelvis motion with high precision even when informing the pitch type was not given. In particular, the time interval from the pelvis angular velocity peak to the impact didn t vary much regardless of the pitch type, as shown in Figure 3b. On the other hand, young batters exhibited large variations in the interval even when the pitch type was notified. angular velocity (squared sum) [rad/sec] Top batter (known condition) impact known -. -. -.... impact Top batter ( condition) -. -. -... time from impact [sec] [s] -. -. -.... Time [s] Young batter (known condition) impact known -. -. -.... impact Young batter ( condition) -. -. -... time from impact [sec] [s] -. -. -.... Time [s] peak time from impact [s] peak time from impact [s] -.8 -. -. -. -.8 -. -. -. fastball Top batter known condition condition Young batter known condition condition change-up Figure 3. Trajectories of the squared sum of angular velocity components of pelvis aligned at impact time (upper left: top batter (known), upper right: young batter (known), lower left: top batter (), lower right: young batter ()); Peak time of pelvis angular velocity of a top batter and a young batter (upper left: top batter (fastball), upper right: top batter (change-up), lower left: young batter (fastball), lower right: young batter (change-up), green: known, blue: )... Sonifying Detected Features of Batting... System Since we found that trunk rotation timing was critical for matching swing to pitch type, we constructed an auditory feedback prototype system that sonified the temporal patterns of batting movement gathered by two compact wireless nine-axes inertial sensors (LP-WSD-A). The system was constructed around two inertial sensors and a receiver connected to a PC, which extracted the data of three-axis acceleration, three-axis angular velocity, and three-axis terrestrial magnetism and synthesized sounds as shown in Figure a. Sampling rate of the two sensors was Hz. One inertial sensor was fixed to a belt so that it was centered over the pelvis of the batter to detect the rotational patterns. The time taken for the squared sum of angular velocity components to peak was calculated; it indicates when the angular velocity was the maximum value. The other sensor was attached to the grip end of the bat by a rubber mount to detect the time of impact; the point at which the squared sum of acceleration is maximum. After each swing, the system converted the calculated peak time and impact time into two synthesized sounds, each was a single sine wave (frequency = Hz, length =.3 s, sampling rate =, Hz).... Sonification Experiment We conducted a pilot sonification experiment to verify whether this feedback approach would be useful for batting practice. As the first step, we presented two sounds and verified whether the participants can pace of the rotational motion in batting. Three expert batters (3.3 ±. years-old) and one beginner person ( years-old) participated. The participants were all male and right-handed. In addition, to examine the applicability to beginners, the same experiment was conducted with one expert man using the non-dominant hand and one female beginner. The experiment was conducted on two days. We conducted a baseline experiment on day one and a feedback experiment on day two. In the baseline experiment, after practice, participants were asked to hit tee balls, toss balls, toss balls, and toss balls in order. Figure b shows a picture

Proceedings 8,, of of tee batting. In the feedback experiment, after practice, participants were asked to hit tee balls, toss balls, toss balls with auditory feedback and toss balls in order. At the beginning of toss batting with auditory feedback, two training sounds were presented in the same way as above and participants were asked to swing so as to reproduce the training sound as closely as possible and keep it constant during toss batting. The training sounds were presented at very short (. s) intervals, from the result of top players batting (Figure 3b). An aluminum softball bat, GNRS3 (SSK), was used ( length:.83m, diameter: 7mm, mass: 7 g ). Tee height and location of the tee were chosen by each participant and toss pitches were generated by a toss-machine. Participants were asked to hit the ball as strongly as possible in all trials. sensor Sensor belt bat Sensor sensor Angular velocity (squared sum) [rad/sec] Feedback system Impact Peak Time from impact [sec] Receiving device PC Peak Impact Figure. Schematic illustration of the sonification system; Experimental scenery (Tee). Prior to processing, all data were smoothed using a fourth-order, zero phase shift, low pass Butterworth filter with a cut-off frequency of Hz. Data recording started s before the swing, and data from s before impact to s after impact were analyzed. Incomplete data and data over mean ± sd were eliminated from the analysis. 3. Results Figure a shows plots of the squared sum of angular velocity components in each phase of one expert participant in baseline experiment and Figure b shows those in feedback experiment. Figure a shows average values of peak time divided by teaching time (. s) of each participant. Figure b shows average values of variations in peak time of each participant. To normalize the variations in peak time, each variation in peak time in toss batting was divided by the variation in peak time in tee batting. Table shows average value and peak time variation, and peak amplitude of each participant at toss batting (second). With regard to peak time, the average value of peak time tended to be long for the expert participants and close to the training value; there was no discernible trend in the variation. Table. Average value and its variation of peak time and peak amplitude at toss batting (second). Batter Average Std. Deviation Average Std. Deviation (Peak Time) [s] (Peak Time) (Peak Value) [rad/s] (Peak Value) (beginner, man).3.3 3.3.87 (expert, man).9.3 8.78.779 3 (expert, man).9.9.7. (expert, man)...7.89 3 with not-dominant hand.83.9 9..7 Beginner, woman.8.3.7.7 Top player, woman....8 Actual batting (known fastball).

Proceedings 8,, of angular velocity (squared sum) [rad/s] -. -... -. -... angular velocity (squared sum) [rad/s] -. -... -. -... -. -... -. -... -. -... -. -... Figure. Trajectories of squared sum of angular velocity components aligned at impact time of one expert participant: Baseline experiment (upper left: tee, upper right: toss (first), lower left: toss (med), lower right: toss (last)); Feedback experiment (upper left: tee, upper right: toss (first), lower left: toss (with feedback), lower right: toss (last)). Each blue dot shows the detected peak of angular velocity in each trial..9.8.7... Beginner 3 With feedback. Tee. Tos (pre) 3.Tos with FB. Tos (post) Baseline. Tee. Tos (first) 3.Tos (second). Tos (third).9.8.7....9.8.7....9.8.7... Experts 3 3 3 Beginner 3 With feedback. Tee/Tee. Tos (pre)/tee 3.Tos with FB/Tee. Tos (post)/tee Baseline. Tee/Tee. Tos (first)/tee 3.Tos (second)/tee. Tos (third)/tee Experts 3 3 3 Figure. Average peak time divided by teaching time (. s) of each participant; Average variations in peak time of each participant.. Discussion The results indicate that the current approach of generating two sounds at peak trunk rotation speed and at impact may make peak time more closely approach the training sound but may not provide much benefit in enhancing batting performance, especially in terms of decreasing the variation in timing. There are two possible reasons, one is that the variation in peak time is not large as it is in actual games. Compared to tee batting, when hitting a pitched ball, it is necessary to judge the course of the ball, which makes the time of swing motion shorter and the variation of time larger. And the other is the interval between peak and impact is too short to be useful. It is still unclear this feedback way can apply for actual batting, so we will conduct an experiment in actual batting in future. Unlike professional athletes, as shown by Table, participants demonstrated larger variation in amplitude than in time at peak trunk rotation speed in this experiment, especially the beginners. Figure 7 shows trajectories of angular velocity in toss batting of the man beginner and woman beginner. Both exhibit large variation in amplitude. Thus it may be better to feedback the magnitude of the amplitude.

Proceedings 8,, of angular velocity (squared sum) [rad/s] angular velocity (squared sum) [rad/s] -. -. -.3 -. -....3.. -. -. -.3 -. -....3.. Figure 7. Trajectories of angular velocity of man beginner aligned at impact time in toss batting; Trajectories of angular velocity of woman beginner aligned at impact time in toss batting. Each blue dot shows the detected peak of angular velocity in each trial.. Conclusions Our goal is to create a convenient self-monitoring system that can be used in daily practice for improving batting skill. To permit daily use, the data logging system must be extremely compact while adequately extracting whole body segment motion. Our previous experiments showed that top and young batters demonstrated different temporal sequences in whole body movement. Such characteristics were acquired by mounting a nine axis sensor at the pelvis. This study developed a sonification system so as to create feedback useful in batting practice. This experiment examined peak trunk rotation time. As a result, this feedback approach could not suppress variations of peak time with toss batting, but may make peak time approach training sound. Also, unlike professional athletes, the variation of amplitude of trunk rotation is large, so it may be effective to convert the amplitude to sound. The significance of this study lies in its simple but powerful data logging system; one sensor on the bat and one at the pelvis. In the future, by combining this with a batting sensing system which measures batting performance, we believe that it is possible to make a more efficient batting improvement system. Acknowledgments: This research is supported by CREST, Japan Science and Technology Agency, Grant Number JPMJCRCRE. References. Welch, C.M.; Banks, S.A.; Cook, F.F.; Draovitch, P. Hitting a baseball: A biomechanical description. J. Orthop. Sports Phys. Ther. 99,, 93.. Sigrist, R.; Georg, R.; Robert, R.; Peter, W. Augmented visual, auditory, haptic, and multimodal feedback in motor learning: A review. Psychon. Bull. Rev. 3,, 3. 3. Sigrist, R.; Fox, S.; Riener, R.; Wolf, P. Benefits of Crank Moment Sonification in Cycling. Procedia Eng., 7, 3 8.. Nasu, D.; Yamaguchi, M.; Fukuda, T.; Saijyo, N.; Kashino, M.; Kimura, T. Perception-action linkage during batting in top athletes. In Proceedings of the Society for Neuroscience 7th Annual Meeting Conference Abstract, Washington, DC, USA, November 7. 8 by the authors; Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/./).