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太极拳虚拟练习体统

太极拳虚拟练习体统
太极拳虚拟练习体统

Training for Physical Tasks in Virtual Environments:Tai Chi Philo Tan Chua Rebecca Crivella Bo Daly Ning Hu Russ Schaaf David Ventura Todd Camill Jessica Hodgins Randy Pausch

Entertainment Technology Center

Carnegie Mellon University

Abstract

We present a wireless virtual reality system and a pro-totype full body Tai Chi training application.Our primary contribution is the creation of a virtual reality system that tracks the full body in a working volume of4meters by5 meters by2.3meters high to produce an animated repre-sentation of the user with42degrees of freedom.This–combined with a lightweight(<3pounds)belt-worn video receiver and head-mounted display–provides a wide area, untethered virtual environment that allows exploration of new application areas.Our secondary contribution is our attempt to show that user interface techniques made possi-ble by such a system can improve training for a full body motor task.We tested several immersive techniques,such as providing multiple copies of a teacher’s body positioned around the student and allowing the student to superimpose his body directly over the virtual teacher.None of these techniques proved signi?cantly better than mimicking tra-ditional Tai Chi instruction,where we provided one virtual teacher directly in front of the student.We consider the im-plications of these?ndings for future motion training tasks. 1Introduction

With recent advancements in wireless technology and motion tracking,virtual environments have the potential to deliver on some of their early promises,creating effective training environments and compelling entertainment expe-riences.In this paper,we describe and evaluate a system for training in a physical task–Tai Chi–and show the ap-plication of training techniques not possible with real world training.

The capture and display system is wireless,freeing the student from the encumbrance of trailing wires.We place a Tai Chi student in a3D rendered environment with a vir-tual instructor,and they learn Tai Chi by mimicking expert motions,similar to real-world Tai Chi instruction.Our hy-pothesis is that virtual environments allow us to take

advan-

Figure1.Left:A student in the Tai Chi trainer.

Right:The virtual world.Student is in light,

teacher in dark clothes

tage of how physical activities such as Tai Chi are currently learned while visually enhancing the learning environment in ways not possible in the real world.The student’s move-ment is recorded with an optical motion capture system that allows real-time capture of the whole body.Captured mo-tion is used to animate representations of the student and teacher and displayed via a wireless head-mounted display (HMD),allowing students to have a natural representation of their body in the virtual environment and easily acquire feedback on their movement.

We view this system as a?rst step toward more effective and general systems for the training of physical tasks.Phys-ical training is an economically important application with a signi?cant impact on both health and safety.VR has great potential for enhancing physical training,with the ability to record a motion once and then replay and practice the motion unlimited times,enabling self-guided training and evaluation.Tai Chi is itself important because there are demonstrated positive effects in preventing falls in the el-derly and other health improvements[22].

We chose Tai Chi because the slow nature of the move-ments and the range of motion?t the properties of our VR system well,additionally we can offer evaluation and feed-back to the student during training.Tai Chi is a challenging training application because the sequence of movements, the form,is complicated and the standards for performance are exacting.Novices struggle to memorize the sequence of movements and more experienced students spend20years or more re?ning their form.Because emphasis is on bal-ance and shape of the body during slow movements,stu-dents are able to adjust their motion based on feedback from the teacher during the sequence.

Figure1shows a user wearing the wireless virtual reality equipment(a belt and an HMD)and the virtual environment with the real-time data applied to a student model.In the virtual environment,the student is rendered with a white shirt and the master wears red.

Real-time,full body capture of the student’s motion allows us to experiment with different forms of visual feedback.We implemented several user interaction tech-niques,such as providing multiple simultaneous copies of the teacher surrounding the student,and allowing the stu-dent to superimpose his body directly inside the teacher’s body.While the former could be done via projection or CA VE-like systems,the latter technique is not readily im-plemented without the use of an HMD.We compared var-ious interfaces objectively by computing the error in limb position between student and teacher,and subjectively via a questionnaire of our subjects.Surprisingly,both the ob-jective measures and subjective questionnaires showed that none of the virtual environment enabling techniques per-formed better than merely mimicking a real world situation, with one teacher in front of the student.

2Background

Wireless virtual environments with full body capture have become possible only in the past few years.To our knowledge,ours is the?rst wireless full body virtual en-vironment system usable for a broad variety of applica-tions.The only other wireless system of which we are aware was a highly specialized dismounted soldier training system that required the participant to wear25pounds of equip-ment[11],severely limiting its applicability.That system was constructed for combat training and used a General Re-ality CyberEye HMD and Premier Wireless for the trans-mittal of a bi-ocular NTSC video image.The motion of the soldier and ri?e were captured with a Datacube optical system.

The technology for wireless whole body capture in real-time has been available for a number of years,?rst with magnetic sensors and more recently with commercial op-tical motion capture systems.Researchers have explored ways to make magnetic systems less burdensome for the user by using fewer sensors and supplementing the data with inverse kinematics for the limbs where motion is not directly measured[2,15,10].The HiBall wireless,wide-area system created by Welch et al.provides very good data but requires the student to wear relatively encumber-ing trackers[21].Technologies for capturing some of the motion of the user via video have also been developed[23].

With the system described in this paper,our goal has been speci?cally to explore the use of virtual environ-ments in training applications.A number of virtual en-vironments have been developed in which the goal is to teach the student decision-making strategies for such situ-ations as hostage negotiations,earthquakes,parachute de-scent and?re?ghting[13,17,6].Fewer virtual environ-ments have been built that attempt to train the user for phys-ical tasks.Emering et al.created a system for action recog-nition that was applied to a martial arts scenario[1].Davis and Blumberg built a virtual aerobics trainer in which the user’s actions were captured and recognized as he or she was instructed to“get moving”or given feedback such as “good job!”[4].The user’s silhouette was captured via in-frared light and matched to a set of pre-recorded templates. However,the effectiveness of the system as a trainer was not assessed.Becker and Pentland built a Tai Chi trainer[3]in a modi?ed version of the Alive[8]system that provided bet-ter depth information.Their system used a hidden Markov Model to interpret the user’s gestures and achieved a greater than90%recognition rate on a small set of18gestures. When gestures were recognized but did not receive a high score,the system provided feedback by playing back the segment of the motion in which the student’s motion dif-fered most from that of the teacher.

Yang performed some preliminary user studies with his virtual environment called“Just Follow Me”[24]using a Ghost metaphor to show the motion of a teacher to a subject. This form of visual feedback is similar to one of our layouts although the rendering styles differed.Subjects executed slow and fast hand motions in one of two test conditions, either while seeing the teacher’s motion displayed in a?rst person view or while viewing the teacher’s motion on a third person video display.Although Yang did not quantitatively assess the results,qualitative assessment indicated that the virtual environment produced more accurate trajectories. 3Training Environment

Our training environment uses the Vicon real-time op-tical motion capture system from Oxford Metrics.The recorded motion is?ltered to reduce noise and recorded for of?ine analysis.The students wear a wireless HMD through which they see a rendered virtual environment containing animated representations of both the student and the teacher.

Figure2.The virtual environment for Tai Chi

X10Transmitter

Reciever

Figure3.Data pipeline and system diagram

The head-mounted display is extremely light,which is im-portant for a task involving body posture.

3.1Virtual World

The virtual environment places the student in a pavil-ion on an island surrounded by a calm lake(Figure2).On the horizon the sun is setting behind the mountains.The environment is designed to be quiet and peaceful as those are the circumstances in which Tai Chi should be practiced. The pavilion also indicates to the student where the motion capture area is.

In the motion capture laboratory,?oor mats are used to demarcate the capture region for the optical motion capture system.To provide further continuity between the real and virtual worlds,the virtual world has a Yin Yang symbol on the?oor in the same place that the symbol appears in the real world painted on a?oor mat.These physical and visual cues allow the student to easily position him or herself in the appropriate part of the laboratory and virtual environment. This positioning is important because the complete Tai Chi form uses the entire available motion capture area.

The student wears a Spandex unitard with re?ective markers applied to the clothing and skin.The student also wears a fabric hip belt that holds the batteries and the re-ceiver for the HMD.These weigh3pounds in total.We use a marker set with4114mm markers,an adaptation of a standard biomechanical marker set.Markers are placed at most joints and along every major bone,and additional markers provide redundant information for critical body segments(head,hands,and feet).When subjects begin the experiment,they are asked to perform a calibration motion in which they move each joint through its full range of mo-tion.The system uses this information to compute a17bone skeleton with bones sized to the correct length for that stu-dent.The setup process–from having the student put on the unitard through calibration–takes approximately30min-utes.

3.2Real-time Optical Motion Capture

Twelve cameras were placed around the laboratory to provide good coverage of a4m×5m capture region2.3m high.The lens of each camera is surrounded by infrared emitters that re?ect IR light off the retrore?ective tape on the markers.The cameras capture1024×1024bitmap im-ages at60fps.These locations on the image plane of each camera are converted to a set of3D points by the Oxford Metrics Vicon512Datastation hardware.

The locations of the markers are sent to the Oxford Met-rics Tarsus real-time server which?ts the student’s skeleton to the three-dimensional marker locations.The?tting pro-cess runs at between30-60fps on a1GHz Pentium III.The variability in frame rate appears to be caused by occasional spurious marker locations produced by the image processor and large changes in the data.

3.3Filtering

After the skeleton has been?t to the capture data,the position and orientation of each limb is?ltered by the real-time server to reduce noise.Because the?tting process oc-curs in real time and must be done very quickly,two types of error are apparent in the output.The?rst is a gross error due to marker mislabeling which causes bones to“?ip”out of position.The other error is a general jittering of the skeleton that results from inaccuracy of the?tting process and marker position reconstruction.Flipping errors,which usually occur during high accelerations,are rare in our sys-tem since Tai Chi motions tend to be slow.Jittering,how-ever,is noticeable regardless of the speed of the student’s motion and needs to be corrected through?ltering.

The mean residual error of markers in the?tting process is between3.9mm and7.2mm for our students(as reported by the Vicon?tting software),enough to cause distracting movement in the virtual environment.In particular when

viewing the environment in?rst-person,where the virtual camera is?xed to the head’s position and orientation,those small errors become large changes in the view.

We chose a Discrete Kalman?lter to reduce the noise in our data because it had been successfully applied in systems and applications similar to ours[20].Sul and his colleagues also used a Kalman?lter to post-process motion capture data to smooth the motion and maintain the kinematic con-straints of a hierarchical model[16].We,however,chose to ignore the bone length constraints during the?ltering pro-cess.This gives acceptable visual results and avoids any extra lag due to the processing time needed to satisfy those constraints.

The Discrete Kalman?lter requires the input signal to be in a linear space.This constraint is not a problem for bone position vectors(which are vectors in R3),but it is a problem for bone orientations(quaternions representing points in S3).In order to apply this?lter to the orientation data we?rst linearize the orientation space using a local linearization technique[7].

Because the virtual camera is?xed to the position and orientation of the student’s head,jitter that may have been unnoticeable on other parts of the body is magni?ed and re-sults in an unacceptably shaky?rst-person view.To correct this,we apply a more aggressive set of?lter parameters to the head position and orientation than to the rest of the body. These parameters make the?rst-person point of view stable without sacri?cing agility in the rest of the body.

3.4Rendering

We chose the Lithtech3.1game engine for our render-ing because it was a fast,robust,and proven engine that supported rendering features critical to our Tai Chi envi-ronment and future environments built with our system: smooth skinned models,custom render styles,and ef?cient networking.

Our rendering application is structured with a client/server model.The server acts as an intermediary, broadcasting commands to control the layout of students and teachers in the environment and the playback position and speed.The server also records data for both the virtual teacher and student for of?ine analysis.The client takes the data from the?ltering application,applies the position and orientation data to an avatar skeleton,and renders the virtual world with the teacher and student models. The client,server,and the?ltering process all reside on a 733MHz Pentium II with a GeForce3graphics accelerator. The rendering speed averages17fps,and is always at least 14fps.

After the scene is rendered,a scan converter changes the signal from VGA to NTSC.The signal is then sent to an off-the-shelf X10wireless video transmitter that broadcasts the video from a location3m above the student’s head in the center of the capture area.This signal is received by an X10video receiver on the student’s belt,and then sent to the Olympus Eye-Trek glasses we use for our HMD.The ren-dering is bi-ocular,with the same image sent to each eye via separate LCD screens.Because a lightweight HMD is re-quired for this application,we had to compromise on spatial resolution of the display itself.The Eye-Trek had a37.5?horizontal and21.7?vertical?eld of view,each screen was 640×360pixels.The weight of the apparatus was3.4oz. Therefore,our decision to degrade VGA to NTSC in order to broadcast it implied little or no further loss of resolution. An important detail in rendering the image for the student is to eliminate other light sources in the laboratory so that the virtual environment is the all the subject sees.We accom-plish this by turning off the lights in the laboratory rather than via a cowling.

3.5Latency

The latency of the motion capture and rendering process was170ms.To measure our end-to-end system latency, we put markers on a rotating disc revolving at60RPM and then added representations of those markers to our existing Tai Chi environment.We then projected the virtual disc image onto the physical disc as it rotated and took pho-tographs to measure the angle between the projected and real markers.The angle difference?θbetween the markers is proportional to latency such that latency=k?θwhere k=60s/(60RPM?2π)=1/2π≈0.159.Our measured?θwas1.1radians,giving us an end-to-end latency of170ms.

A latency of170ms is high for an interactive virtual en-vironment,but the effect on the student’s performance is somewhat mitigated by the slow nature of movements in Tai Chi.In addition,the students tend to lag behind the teacher by an average of610ms as described in section4.2.

4Assessment

In order to evaluate the effectiveness of our system for learning Tai Chi,we tested40volunteers to analyze how well they learned the motions of a previously recorded teacher,given different visual user interfaces involving the teacher and student in the virtual space.

There are a large number of design choices for represent-ing the student and teacher in a full body motion training task.We made the constraining assumptions that the stu-dent would always see a?rst-person view,that the teacher and student would be represented in a fairly realistic way (both would remain humanoid,be of the correct propor-tions,etc.),and that the feedback that the students received would be entirely visual and based on body positions alone. We also?xed the orientation of the teacher and student so

(a)One on

One(b)Four

Teachers(c)Side by

Side

(d)Superimposition

1(e)Superimposition2

Figure4.The?ve conditions

that they faced that same direction.This decision was based

both on early pilot studies and the fact that traditional Tai

Chi classes are taught this way.After a number of pilot

experiments,we identi?ed?ve representative points in the

design space(Figure4).

?One on One:One teacher with one student

?Four Teachers:Four teachers surrounding one student

?Side By Side:Four teachers standing next to four stu-

dents with one student in the center.

?Superimposition1:Five normally rendered students

with a red wireframe teacher superimposed on them.

?Superimposition2:Five wireframe and transparent

green students with a red stick?gure teacher superim-

posed inside them.

4.1Experiment Design

The majority of our40volunteers were college students

with no previous formal motion training.Each subject ex-

perienced four randomized(layout,motion)pairs where the

layout was one of the?ve in Figure4and the motion was

one of the four described below.There were originally only

four layouts;the?fth,Superimposition2,was added late

in the experiment.Based on early subject feedback regard-

ing the rendering of Superimposition1,we chose to test an

alternate rendering method with the same general layout.

No subject repeated a layout or a motion.The order in

which the students saw the layouts and motions was ran-

domized to minimize any learning effects between motions.

For each(layout,motion)pair,subjects were asked to match

the teacher as they performed twelve repetitions of the same

motion after watching the motion from any viewpoint the

subject chose.Subjects were told when six repetitions re-

mained and when four repetitions remained.

All four motion animations were segments of the same

Tai Chi form performed by a Tai Chi teacher and captured in

an of?ine motion capture session.Each motion was approx-

imately twenty seconds long and had distinguishing charac-

teristics.Motion1featured simple hand movements and a

90degree turn to the right;motion2had little hand mo-

tion,a180degree turn of the feet,and some turning of

the upper body;motion3featured slow hand movements,

large movement of the feet,and some turning of the tho-

rax;and motion4featured swift hand movement and turn-

ing of the thorax and hips but little movement of the feet.

Based on participants’error measurements,we can say that

all motions were of approximately equal dif?culty except

for motion1which was signi?cantly easier(Figure5(b)).

4.2Results

In order to measure how closely the student mimicked

the teacher’s motion we used12bones for comparison:the

upper and lower arms,hands,upper and lower legs,and

feet.Each bone was de?ned using the skeleton’s hierarchy

with a parent end and a child end.For example the upper

arm had a parent end corresponding to the shoulder and a

child end corresponding to the elbow.We measured the

error for each bone as the difference between teacher and

student child end positions,once the parent end positions

and bone lengths had been normalized.Given student bone

E r r o r

(a)Learning Effects

E r r o r (b)Motion

Dif?culty E r r o r

(c)Layout Comparison

Figure 5.Error analysis results.Error bars show 95%con?dence interval.

end positions S p and S c and teacher bone end positions T p and T c the error E for that bone was:

E limb = S c ?S p S c ?S p ?T c ?T p T c ?T p

We then average the errors over all limbs to get the

total error for one frame of data:E f rame =∑12i =1E limb (i )/12.To obtain the total error for one repetition of the motion,we summed over the n frames in that repetition:E rep =∑n j =1E f rame (j )/n .

Finally,though there are 12repetitions for each motion,we considered only the last four that the students performed.Before the 9th trial,subjects were reminded that there were four repetitions remaining and encouraged to do their best on the remaining trials.Averaging over these four gives a reasonable indication of how well the student learned the form.So the total error,for one student,given one layout and one motion,is E trial =∑12k =9E rep (k )/44.2.1

Data Analysis Details

The error measurement for full motions was slightly more complicated.There were two major sources of error which were common for all students who participated in the ex-periment:time lag and yaw offset.If the student was not oriented in precisely the same way as the teacher,the error in yaw would add an additional error to all bones in the student’s body.Even if the student performed the form per-fectly,if there was a few degree offset in the orientation the student would have a large error.To minimize this,we considered the student’s starting pose and found the yaw offset that minimized this static pose error.We found that

E r r o r (a)Yaw Shift (degrees)

E r r o r

(b)Time Shift (s)

Figure 6.Change in error with yaw and time shifting

when considering all possible offset angles,from ?30?to 30?there was one clear point where error was minimized (Figure 6(a)shows a typical case).

In addition to the yaw shift,as the students performed the motion they all tended to lag behind the master.Be-cause they were still doing the motion correctly,just not at the same time as the master,we searched for a time shift that would minimize this error.For each repetition of the motion,we considered all possible time shifts from 0to 120frames (0to 2seconds).For each value,we compared the shifted student data with the original teacher data to get the error value.Again we found that there was one clear shift value which minimized the error (Figure 6(b)shows a typi-cal case).The average time shift was approximately 610ms.We also needed to make sure there was no learning or fatigue effect.Figure 5(a)shows that when we averaged all conditions performed ?rst,second,third,and fourth across all subjects,the order of performance had no effect on er-ror.Before we could average results from different mo-tions we needed to compensate for different dif?culties in the motions.Figure 5(b)shows that for the average across all subjects,motion 1was signi?cantly easier than the other motions.For our ?nal analysis,we normalized the error values based on the mean dif?culty of each motion.

Having dealt with these issues,we can now compare all of the layouts with each other.Figure 5(c)shows the average error across all subjects for each layout.The N varies for each of the layouts because Superimposition 2was added later in the experiment and some subjects were unable to do all four (layout,motion)tests due to lack of time,discomfort,and other reasons.The only statistically signi?cant conclusion we can draw based on the 95%con-?dence intervals for the average errors is that Superimpo-sition 1is worse than the others by a small amount.One on One,which most closely mimics a traditional teaching environment,is as good as the other techniques.4.2.2

Questionnaire Results

After each experiment ended,we gave a questionnaire to the subjects.We asked them to rank the four layouts they expe-

One On One (n =30)(n =23)(n =26)(n =27)Super.2(n =6)

%S t u d e n t s

Easiest Hardest Figure 7.Questionnaire Results:Layout Dif-?culty

rienced,from easiest to hardest.As Figure 7shows,the two Superimposition trials were considered to be signi?cantly harder than the other trials.In fact,all of the subjects who tried Superimposition 2thought it was the most dif?cult.In-terestingly,although subjects considered Superimposition 2very dif?cult compared to the other layouts,average error on that layout was not signi?cantly greater than the other non-superimposed layouts.

5Conclusions

Our primary contribution is the engineering of a wireless virtual reality system that tracks 41points on the human body in a working volume of 4meters by 5meters by 2.3meters high.Our system has a positional accuracy of roughly 5mm,a latency of 170ms,and maintains a ren-dering frame rate of 17fps using a commodity https://www.doczj.com/doc/5d16075540.html,ing a light sunglasses-style HMD and a 3pound waist pack,ours is the ?rst wireless virtual environment system useful for a large variety of applications.

To our surprise,none of the layouts of students and teachers had a substantial effect on learning a motor con-trol task involving full body motion.This result contradicts the initial intuition of virtual reality researchers with which we have discussed this project.They generally assumed su-perimposition would make the task much easier.If other studies come to similar conclusions for other motor con-trol tasks,the virtual environment research community may need to more carefully examine which tasks are best suited for immersive training,as full body motion motor tasks are often cited as example applications.

We have several theories about why the VR-only tech-

niques fared no better than our simulation of real-world instruction (the One on One layout).In our experiments,students were expected to perform motor movements while simultaneously watching the movements of the teacher’s avatar.Other studies of simpler movements have indicated that this simultaneous activity may interfere with learn-ing [12,14].Pomplun and Mataric compared the per-formance of subjects making arm movements when the subjects were instructed to rehearse while watching a video presentation of the motion and when they were instructed to just watch the video before performing the task [12].The subjects who did not rehearse performed substantially better.

Ellis et al.showed that system latency is highly corre-lated with performance in a virtual reality tracking task [5]and Ware and Balakrishnan show that mean time for static target acquisition is directly proportional to latency [19].Although our latency is admittedly large,we chose a slow task so that latency effects would be small.We also mea-sured our errors with a technique that should account for the students’latencies in responding to the teacher.It would have bene?ted our experiment to understand how our la-tency –and by extension other factors such as ?eld of view and frame rate –affected performance,and what amount of latency is acceptable for a motion training task such as ours.With the exception of the superimposition layouts,our rendering styles were chosen to represent the student and teacher in as realistic a fashion as possible given the limited polygon count possible in a virtual environment.However,experimental evidence indicates that subjects tend to track the hands when watching or imitating a teacher performing arm movements [9].If these results generalize to Tai Chi,a rendering style that emphasized the position and orientation of the hands might be more effective.

We evaluated the motion of the students during trials 9-12in the virtual environment.A better evaluation technique would have been to remove the visual stimulus of the images of the teacher and student and assess the stu-dent’s unaided performance [14].In addition to assessing retention in the absence of feedback,this assessment tech-nique would have allowed us to compare the effectiveness of more standard visual presentations such as a video of a teacher projected on the wall of the laboratory and perhaps understand whether the small ?eld of view and low resolu-tion of the HMD were affecting the student’s ability to learn in the environment.

We can not conclusively rule out that our virtual envi-ronment was at fault;one can always worry that if only our ?delity had been better,the latency had been lower,or we had just been clever enough to try another rendering style or user interface,the results would be different.However,our system is substantially better in both tracking area and spatial resolution than most full body tracking systems,and

addresses what has been identi?ed as one of the biggest re-maining problems:the umbilical cord[18].Therefore,we can at least conclude that if virtual environments are to be helpful for this task,they must either be at higher quality that we have engineered,or utilize better user interaction techniques than we devised,or both.

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24式太极拳分解教学

24式太极拳分解教学 关键词 : 24式太极拳 一、起式 1 2 3 4 5 二、左右野马分鬃 6 7 8 9 10 11 12 13 14 15 16 三、白鹤亮翅

17 18 19 20 21 22 23 四、左右搂膝拗步 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 五、手挥琵 琶 39 40 41 六、左右倒卷肱 42

43 44 45 46 47 48 49 50 51 52 53 54 第一集 | 第二集 | 第三集 | 视频演练 传统武式太极拳练习五阶段 太极是一门学问,它要求人们客观、辩证、一分为二地对待事物、看待问题、分析问题、解决问题。它是以万事、万物的本身皆有既互相对立又互相统一的哲理为基础的一种思想认识。我们把这种对待事物的思想认识称为太极思想。武式太极拳是太极思想与人体运动相结合的具体表现。它是一个科学的人体辩证运动过程,在这个运动过程中势势处处、时时刻刻都包涵、体现着人体内的阴阳变换、虚实相间和刚柔相济。武式太极拳的训练注重整体身法和气势,要求举手投足立身中正、松静自然、虚实清楚、上下贯穿、八面支撑。它对身法的要求极严、极细、极微、极妙,无一不符合人体的科学要求和规范,正如乔松茂先生所言“……它科学地集拳术、力学、导引、传统哲学为一体”。凡学者只有严守身法——立身中正,充分努力地体现出这一风格和特点来,由学架子到改架子;由改架子到走顺架子;由走顺架子到技击的运用;由技击的运用到无畏无敌的精神境界。它是一个循序渐进、节节升高、逐步完成和长功的过程,它须在师父的正确的言传身教下通过自己的不懈努力才能步步提高。它不仅仅是身体的简单运动,更重要的是内在的精神冶炼、身心合一。它的外形功架势势符合力学的科学原理,它的内涵机理处处渗透着人体机能的运动规律,它势势均与拳理接骨斗榫、毫厘不差。练功走架的感觉如咖啡提神又如美酒陶醉,只要坚持按要求锻炼就可形成太极身法,必能达到固本培元、增强体质、防身御敌、技艺超群和祛病延年之功效。 练武式太极拳原本没有阶段划分,或准确的讲,它的阶段之间是相互渗透不可以分得清清楚楚的,是一个逐步提高的过程。这里为了学者便于掌握,让初学者在心中有一个大概的框架,本人根据个人体会将练习功架的过程分五个阶段来阐述,以便同好参考

练习太极拳的主要过程及其要点

练习太极拳的主要过程及其要点 练习太极拳和其它体育项目一样,要经过一个由生到熟、由熟到巧的逐步提高的过程。 太极拳有独特的运动特点和风格,只有充分体现出这种风格特点,使每一姿势动作符合要领,才能更好地收到增强体质的功效。 大致说来,练太极拳可以分成三个阶段。第一阶段,应该在姿势(完成式)、动作(过滤式)上打好基础,把拳套中的步型、步法、腿法、身法、手型、手法、眼神等基本要求弄清楚,做到姿势正确,步法稳定,动作舒展、柔和。第二阶段,注意掌握动作的变化规律及其特点,做到连贯协调,圆活自然。第三阶段着重练习劲力的运用和意念、呼吸与动作的自然结合,做到动作轻灵沉着,周身完整统一。 在全部锻炼过程中,不管哪一阶段、哪一步,都要注意保持“心静”、“体松”两个基本要领。心静、体松是太极拳运动特点所决定的最基本的要求,它对于其它要领的掌握起着保证作用,应该贯注于练太极拳的全过程。“心静”就是指思想集中,精神贯注,做到专心打拳。“体松”是指身体各部位保持运动中的自然,排除不必要的紧张。正确运用这两个要点,有利于掌握太极拳的其它要领,体现太极拳的运动特点,提高健身和医疗的效果。因此有人把“松”“静”两点作为打好太极拳的基本条件。 在练习太极拳的不同阶段,对“松”“静”这个基本要求的掌握也是从低到高,逐步加深体会的,它和技术练习的要求紧密地联系在一起,两个方面不可割裂对待。

下面把练习太极拳的主要过程及其要点,简述如下。 第一阶段 属于打基础阶段,要注意以下几个要点: (一)端正 打太极拳首先要注意姿势正确,特别要保持上体自然正直,腰脊中正,两肩、两胯自 然放松,不可俯仰歪斜,或耸肩膀、扭胯。其它部位也要按照要求切实做好(参照前“对身体各部位姿势的要求”部分)。忽视任何一个部位的要领,必然牵其它部位,造成错误定型和错误动作。例如姿势中臀部外突,必然牵连腰部和胸部前挺,腹肌紧张。因此,初学阶段要抓住姿势“端正”这一环节,不可贪多求快,潦草从事。这样做开始阶段可能刻板一些,初练起来灵活性稍差,但只要抓住了“身法”中的主要矛盾,其它问题,以后容易解决。 (二)稳定 要使上体端正舒适,必须首先保持下肢稳定。步型、步法既是姿势当中的一部分,又是整个姿势的基础。经验证明,很多人下肢不稳,并不完全出于力量不足,而多数是由于步型、步法不当。如果步子过小过窄,或脚的位置、角度不对,以及变换动作时虚实不清,势必造成身体重心不稳。因此必须把步型、步法的要求弄清楚,可以单练各种桩步和步法,先把身体重心的变换找清楚。这样既利于培养下肢的支撑力量,又能把主要步型(弓步、虚步、仆步、独立步等)、步法(进步、退步、侧步、跟步等)的要领掌握好。此外,根据具体情况,

杨氏太极拳名家实战用法

2008-07-31 13:20 起势实战用法(口诀:全体大用意为主体松气固神在凝) 1、杨澄甫: 此为预备动作之姿势,……尤要精神内因。气沉丹田,一任自然,不可牵强,守我之静,以待人之动,则内外合一,体用兼全。人皆于此势易为忽略,殊不知练法用法,俱根本于此。 2、牛春明: 预备动作,灵活运用。 两臂上提是掤劲,即用掤劲接住(粘住)以待势反击,下落是采劲,采敌来力,化力借用,有四两拨千斤之用。 3、李雅轩传授陈龙骧李敏弟: 起势以安静心神,养其虚灵之气,以备对方不测之来手,周身各部都可相机而动,切勿轻视之。 4、崔毅士传授崔仲三: 用法(1):对方双手死握我双腕下压,我顺势向下沉肩,缷对方之力。趁着对方回抽瞬间,我力发于肢,提髋紧腰,双臂向前提起送出,破坏对方重心,使之向后倾倒。 用法(2):再如对方双掌向我迎面扑来,或如对方双掌抓我双肩,我以双肩虎口向上接应对方双肘或双臂下侧,将对方向后掀起,随之用双掌攻击对方胸部。 用法(3):对方正手或反手握我双腕,我松腰沉髋,沉肩垂肘,以挑掌动作结合弧形路线,赂内引进化解;使之身体重心前倾,脚跟拔起,力量落空。 用法(4):结合上势动作,我虽已破坏对方重心,但未解脱,此时,我即刻向下、向两侧分掌,使对方处于被动局面,在对方想撤手变化之时,我随之放长击远,双掌向对方胸部推按,以脚、脚、腰之力将对方推出。 用法(5):我双手进攻对方胸部,对方处于被动局面,对方由内外分拨我双掌时,我即时松肩肘,双手拿住对方双腕,迅速下落使之身体重心前倾,趁对方身体前倾时,起腿以膝关节顶撞对方。

发表于2008-08-01 09:18 揽雀尾(掤、捋、挤、按)实战用法(口诀:掤捋挤按雀尾生) (一)左掤右掤实战用法 1、杨振基: 《太极体用全书》上说:“敌人对面用左手击我胸部,我……以我之腕贴在彼之肘腕中间,用横劲向前往上掤去。”这里的掤法是向前向上转腰横出,用的是横劲。 掤手是杨式拳的总手之一,也是推手中的接手。意念在腕的上缘,打手时一般以腕部与人相接,劲点也在腕的上缘。掤手在杨式太极拳中使用最多,也最有效。 2、杨振铎: 左掤:设对方以右掌或拳向我击来,我即将左臂提起,用掤劲(粘劲)将对方之臂架起,使其不得接近我胸,如果以腰带臂,使臂、手齐向外翻,变掌心向外,即可将对方之臂握住,利用采劲将其力引化至一侧,使其落空,失去重心,必为我制。 右掤(双手掤):设对方以左掌向我击来,我急上右腿,以右臂置对方左臂近肘处,并以左手掌心侧向外,接住对方腕部,握住对方手腕,再以右臂向上掤起,而左手在下面用采的手法向下采,再加以按劲,此时就会使对方两臂之间的肘部处于上提、下压被撅之势,轻则被动双脚离地,重则定被撅断臂。 3、郑曼青传授黄性贤: 实战中,如右手抓住对方右手腕,则上左步,此时有两种击法; 用法(1):如自己左手在对方手臂下,则用左小臂横劲对方胸腋部; 用法(2):如果自己左手在对方手臂上,则用左手臂掤对方臂部及胸口。 4、董英杰传授董虎岭: 对方从右侧面左拳打我胁部,我速向右转身,同时右手抬起将其拨开。对方继续用右手击我胸部,我左手提起将其掤开,同时左脚横迈一步,弓腿,两腿坐实。避过对方攻势后,我右手从下往内绕一小圈,转到对方胸部,右脚上步弓腿,全身整劲向其掤去。 (二)捋式的实战用法 1、杨振基: 《太极拳体用全书》上说:“设敌人用左手击我侧肋部……速将我右腕肘间,侧贴彼肘节上,侧仰左腕,以腕背粘彼之腕背臂上……内向胸前、左侧捋来”。捋是拖腕捋肘,施用时,顺对方的来力,向里引进,使对方力量落空,即转腰将对方向一侧捋出。 捋对方的手臂时要管住对方的腕、肘关节。杨式太极拳在推手中有一条重要原则是管活的,不管死的。意思是管住了对方身上活动的关节,则对方转动不灵,不易走化。就手臂而言,腕和肘是活动的关节,捋对方时,管住了这两个关节,就容易拿住对方。 捋式右手意念在手掌,劲点在掌下缘。左手意念在手背,劲点在手背或虎口处。实施捋法时,注意与对方“贴随”,因为捋时左手是用手背粘人,必须与对方贴住。才能随对方的变化而变化。粘连贴随这里重点突出“贴随”二字。

学校太极拳队训练计划

学校太极拳队训练计划 - 一、学校开展太极拳运动的重要意义: 中国古老的太极拳,既是武术,又是文化;既是健身术,又是护身术;它既练内(心)又练外(体),精、气、神兼顾;既有养生健身价值,又有艺术欣赏价值,因而受到越来越多人的欢迎.太极拳非常重视加大人体下部运动量,大大有利于避免上盛下虚的“时代病”.太极拳不仅强调肢体放松,而且练拳全过程都要求精神放松,使大脑抑制与兴奋相结合,从而它还有利于心态平衡.所以,针对当今生活方式,练习太极拳是一条非常可靠的身心健康之路.只要天天练太极拳,就可以使你持久地保持身心健康. 太极拳的魅力,已经吸引了整个世界,它不仅是作为中国特有的民族体育运动项目,也是一项世界性的运动项目,欧美、东南亚、日本等国家和地区,都有太极拳的运动.纵观太极拳开展与研究现状,我们不难发现,开展太极拳活动的基本上集中在中老年,尤其是老年人的活动.少有在青少年中开展,特别是在学校开展太极拳的教育几乎没有.增强青少年体质、促进青少年健康成长,是关系到国家和民族未来的大事.以二零零八年北京奥运会圆满成功为契机,进一步加强青少年体育、增强青少年体质,对于全面落实科学发展观,深入贯彻党的教育方针,大力推进素质教育,培养中国特色社会主义事业的合格建设者和接班人,具有重要意义.为此,我校确立了太极拳普及教育的实践研究. 二、开展太极拳运动的措施: 1、内容:在线学习《杨氏三十八式太极拳》的基础上,本学期学习《二十四式太极拳》,深化太极拳的演练水平. 2、聘请柴师傅为学校的太极拳队顾问,有计划、循序渐进的对师生进行武德、武艺、武理等方面的训练. 3、选择部分年级的学生进行太极拳教学的试点,总结经验后,逐步地在全校进行推广. 4、确定具体的时间安排: 每周我们安排一节体育课、对试点年级的各班进行基本套路教学; 每周安排一次课外活动时间进行集体的太极拳巩固练习; 每周安排一次课余时间,针对试点年级中部分优秀学生进行提高性练习.同时安排一定的课外活动时间进行练习,使得我校的每一位教师至少掌握一套太极拳的套路,在校每一名学生在初中毕业之前至少都能够学会一套太极拳,增强健身意识,提高健身技能,增强师生身体素质. 4、通过专题教育活动——“阳光体育运动”,强化学生学习太极拳的技能.组织竞赛活动,培植兴趣、提高技能,并通过各种形式激励,发展兴趣特长. -

太极拳试题(附答案)

太极拳专项课试题 1.武术的作用是_A___。 A强身健体, 娱乐休闲,修身养性,防身自卫.B引人关注C可以占强 2.武术比赛采用 A 计分方法。 A.10分制记分. B.100分制记分 C.5分制记分 3.武术的比赛场地是 B 。 A .长12米宽6米 B.长14米宽8米 C.长9米宽9米 4.武术包含 C 内容。 A击剑B摔跤 C 拳术,器械,对练,散打和其它. 5.武术的主要器械是 A 。 A刀,枪,剑,棍B暗器C弓箭 6.简化太极拳有 C 式。 A16式B30 C24 7.北京奥运会的吉祥物名称是福娃贝贝、京京、欢欢、迎迎、妮妮,五个字的谐音是 C 。 A中国欢迎您 B 首都欢迎你C北京欢迎您 8.太极拳动作特点是处处带有形, 练习时也对身体和心理有要求, 正确答案是 B 。 A正形体紧注意 B 弧形、体松、心静C随意紧张安心 9.饭后 C 再进行运动较为适宜。 A半小时B十分钟 C 1 小时 10运动中和运动后的饮水, 应 B 为原则。 A随意B少量多次C多量多次 11.简化太极拳24式中唯一一式用脚跟点地的动作叫是C 。 A 独立B海底针C手挥琵琶 12.太极拳有多种流派,在河南的是 B 。 A杨式B陈式C吴式 13.简化太极24式的练习时长是 A 。 A:五到六分钟左右.B八分钟C十分钟 14.马步两脚之间的宽度是 B 。

A随意 B 三脚半长C二脚长 15.武术的步法中____B___是最省力的? A 马步B歇步C弓步 16. 15.武术的步法中____C___是最费力的? A 马步B歇步C虚步 17.太极拳中的”太极”有 C 含意? A很高B很深奥C无穷大 18拳有拳心,拳眼,拳面,拳轮和拳背要素,拳的大拇指应压放在中指食指的B 。 A第一指节B第二指C随意 19武术有 B 主要步法。 A很多B五种C四种 20武术有___B_____主要手法。 A很多B三种C五种 21太极拳运动后是否能马上用凉水洗手或冲凉B_______.。 A.能 B 不能C无严格要求 22.简化太极拳是在 A 的基础上发展起来的。 A.杨氏太极拳 B.陈氏太极拳 C.孙氏太极拳 23.二十四式简化太极拳分为 C 组。 A.5组 B.7组 C.8组 24.二十四式太极拳第三式为__A______。 A.白鹤亮翅 B.手挥琵琶 C.左右倒卷肱 25.简化太极拳的动作是以 A 的原则。 A.由简入繁,先易后难B.由繁入简,先难后易C.随机性 26.太极拳动作的特点是 A 。 A.柔和、缓慢、圆活、连贯B.舒缓、连贯C.柔和、圆活 27.太极拳动作的运行路线是 C 。 A.如行云流水,连绵不绝B.刚劲有力,连贯自如 C.处处带有弧形,如行云流水,连绵不绝. 28.简化太极拳24式第四式是 C 。

什么时候练习太极拳最合适

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时间,甚至可以化整为零,分几次练习,同样有效。 夏季练太极拳的原则和好处 随着夏天的到来,早晨天亮的时间越来越早,天气也越来越暖。很多人都开始了晨练,而太极拳受到了大多数中老年人的喜爱。那么,今天就和大家来介绍一下练习太极拳的原则和好处都有哪些吧。 练习太极拳的原则 中医学认为气、血是构成人体的基本物质,是人体脏腑、经络、组织器官活动的物质基础。气为血帅,血为气母,气血的调和与通畅是人体健康的关键。太极拳着重于对精、气、神的修练,尤其在锻炼时要求以意导体、以体导气,从而使气血运行流畅而致平和。因此常见一般练习太极拳有年之人,即使在冬天在户外打拳,也无需戴手套,练习后手还是暖暖的。这仅说明练习太极拳能促进气血运行的只鳞片甲而已。 中医学将气归纳成:元气、宗气、营气、卫气;其中元气是人体生命的原动力。宗气是水谷精微之气与大自然空气的混合体,积于胸中,以补充元气。营气行于脉中,濡养五脏六腑、四肢百骸。卫气行于脉外,有温分肉、肥奏理、司开合的作用。它们的协同作用,保证了血脉的畅通,维持了人体周身各部的功能作用。 太极拳则将元气、宗气、营气流归成内气,将卫气归为外气,通过养、蓄、运、使四个方面来练气养生。尤其是吴图南师爷提出的养蓄宗气、培补元气。运行营气、开发卫气,更是太极拳养生保健的关要之说。 接下来,再来看看联想太极拳的好处是什么。

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练习太极拳的六个基本功

练习太极拳的六个基本功 对于没有任何学拳基础的人来说。练习太极拳就要从零开始学起,不是说练习太极拳不需要基础,而是练习太极拳的最重要的就是基础的练习,只有学好了基础才能提高你的太极拳。 一、无极桩 首先将双脚分开要与肩同宽,将你的双膝微微弯曲,身体的重心放在两条腿上;将双手就到胸前微微弯曲手臂,手指呈自然装展开,手指指尖相对,手掌掌心向里呈现抱球状,两眼注视双手。姿势高低可根据体质和腿部力量自行掌握,通过练习下部力量增加稳实,周身内劲饱满,丹田之气充足。 二、开合桩 在无极桩姿势的基础上,两手臂作稍向外棚开和稍向内收合的练习。开时为吸气(小腹鼓起);合时为呼气(小腹内收)。初练时呼吸应力求自然畅通,不要勉强憋气。当练久之后,可以加大呼吸程度,扩大充气量。如吸到极点不能再吸时,改为呼气。同样,呼到极点将气全部吐出不能再呼时,改为吸气。每次可练3-5分钟,日久可渐增。 三、升降桩 预备时,身体自然正直,两脚开立,头正悬顶,下颏微收,肩臂松垂,两手轻贴大腿外侧,眼向前平视。这时体松心静、排除杂念、精神集中、呼吸自然。动作时,两手缓缓向前平举至肩高,同肩宽,两肘微下垂,手指微屈,指尖向前,手心向下,眼看两手方向。 这时为吸气(小腹内收,意由丹田提气上升,贴于脊背)。用意不用力,自然稳重,此为“升”式。当两手臂升至肩高时,转为下落,两手按至腹前,手心向下,微微下塌,舒指展掌,眼看前下方。 这时为呼气(小腹鼓起),气沉丹田,此为“降”式。这样两手臂随两腿的屈伸,做前平举和下按的反复练习即为“升降”练习。姿势的高低可根据体质情况和腿部力量自行掌握。

初练时呼吸应力求自然畅通,不要勉强憋气,久练后可以逐渐加大呼吸量。如两手升至肩高,吸到极点不能再吸时,改为呼气。同样两手下按,呼气到极点不能再呼时,改为吸气。一升一降为一次练习。初练时,可做3-5次,久练后,练习的次数可逐渐增加。 四、虚步桩 首先身体立正真好,身体的重心移到右腿上,并将右腿微微弯曲,左腿向前迈出半步用脚跟点地将脚尖翘起,然后将左膝微微弯曲的同时将双手举向前放,将左手上举同鼻子高度,右手放于左边肋骨的下方,双手手指微微弯曲,自然分开,掌心斜相对,指尖均朝前上方,眼看左掌方向,如同左琵琶式。

杨氏太极拳名家实战用法总结

杨氏太极拳名家实战用法总结 一、起势实战用法(口诀:全体大用意为主体松气固神在凝) 1、杨澄甫: 此为预备动作之姿势,……尤要精神内因。气沉丹田,一任自然,不可牵强,守我之静,以待人之动,则内外合一,体用兼全。人皆于此势易为忽略,殊不知练法用法,俱根本于此。 2、牛春明: 预备动作,灵活运用。两臂上提是掤劲,即用掤劲接住(粘住)以待势反击,下落是采劲,采敌来力,化力借用,有四两拨千斤之用。 3、李雅轩传授陈龙骧 李敏弟: 起势以安静心神,养其虚灵之气,以备对方不测之来手,周身各部都可相机而动,切勿轻视之。 4、崔毅士传授崔仲三: 用法(1):对方双手死握我双腕下压,我顺势向下沉肩,缷对方之力。趁着对方回抽瞬间,我力发于肢,提髋紧腰,双臂向前提起送出,破坏对方重心,使之向后倾倒。 用法(2):再如对方双掌向我迎面扑来,或如对方双掌抓我双肩,我以双肩虎口向上接应对方双肘或双臂下侧,将对方向后掀起,随之用双掌攻击对方胸部。

用法(3):对方正手或反手握我双腕,我松腰沉髋,沉肩垂肘,以挑掌动作结合弧形路线,赂内引进化解;使之身体重心前倾,脚跟拔起,力量落空。 用法(4):结合上势动作,我虽已破坏对方重心,但未解脱, 此时,我即刻向下、向两侧分掌,使对方处于被动局面,在对方想撤手变化之时,我随之放长击远,双掌向对方胸部推按,以脚、脚、腰之力将对方推出。 用法(5):我双手进攻对方胸部,对方处于被动局面,对方由 内外分拨我双掌时,我即时松肩肘,双手拿住对方双腕,迅速下落使之身体重心前倾,趁对方身体前倾时,起腿以膝关节顶撞对方。 二、揽雀尾(掤、捋、挤、按)实战用法(口诀:掤捋挤按雀尾生) (一)左掤右掤实战用法 1、杨振基: 《太极体用全书》上说:“敌人对面用左手击我胸部,我……以我之腕贴在彼之肘腕中间,用横劲向前往上掤去。”这里的掤法是向前向上转腰横出,用的是横劲。 掤手是杨式拳的总手之一,也是推手中的接手。意念在腕的上缘,打手时一般以腕部与人相接,劲点也在腕的上缘。掤手在杨式太极拳中使用最多,也最有效。2、杨振铎:

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