Hand Biomechanics Skilled Pianists and Use of the Data for ...
Transcript of Hand Biomechanics Skilled Pianists and Use of the Data for ...
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American Osteopathic Academy of Sports Medicine
29th Annual Clinical Conference • March 19-22, 2014 • Westin Tampa
Harbour Island Hotel • Tampa, Florida
Snowmass, CO
Hand Biomechanics of Skilled Pianists
and Preventive and Rehabilitative Strategy for Pain and Injury
University of South Florida Sang-Hie Lee, PhD, EdD, MM
Collaborators: Angel Luciano, MD; Jeffrey Chodil, MM; Yun Lin, PhD candidate; Yu
Sun, PhD, This research was supported by USF Neuroscience Collaborative Grant
Order of Slides
l Slides #4 – 7 Introduction l Slides #8 – 12 Literature l Slides #13 – 36 Study l Slides #37 – 48 Cases l Slides #49 – 50 “Peanuts play”
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Skilled Pianists Hands
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Premises
l Skilled pianists’ hand dexterity involves precise finger-touch control and efficient bodily support to produce the desired tones.
l Pianists’ hand come in varied size and shape. l We developed hand measurement-- static
biometrics, dynamic range of motion, and motion capture and compared the hand data with performance data (MIDI).
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Questions l Are there differences in hand biomechanics among
different classification of pianists as results of their training?
l Are there relationships between hand biomechanics and performance quality?
l Are the relationships vary among the four groups? l Are there differences in performance quality among the
classifications? l Does sex influence biomechanics and performance, and
does it factor in the relationships between them?
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Demystifying Pianists’ Hands “Liszt hands were large.”
l Liszt’s had “deep-lying connective tissues between the fingers” which gave him superb finger independence (Kentner 1976).
“Accomplished pianists all have long fingers.”
l Busoni, Rachmaninoff, Rosenthal, and Saur had long fingers, while d’Albert, Reisnauer, Teresa Carreno, and Pachmann, had short ones (Kentner 1976).
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Otto Ortmann (1929, 1962, 1984)
l An adult pianist with a smaller hand and larger hand span (127°) had the pianistic advantage over a pianist with a large hand and smaller hand span (75°).
l A child’s hand—generally featuring a small span between the thumb and index finger, high webs between fingers 2–3, 3–4, and 4–5, a small span between fingers 1 and 5, and a lesser range of movement at the wrist—is an example of a disadvantageous piano-playing hand.
l A same-age child with all the opposing biomechanical features made more rapid progress, possibly attributable to the biomechanical advantage.
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Christoph Wagner (1988, 2006)
l Analyzed 238 pianists’ biomechanical data.
l Pianists’ left hand spans were significantly greater than the right hand.
l Ranges of both active movement --flexion of the metacarpophalangeal (MCP) joint, wrist abduction, and forearm pronosupination, and passive movements-- were greater in female than male.
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Lee study (1990)
l Lee study of 13 skilled pianists concluded that wrist mobility in the ulnar direction and spans involving all fingers were factors relating to good piano performance.
¡ Chopin Etude Op.10 # 1 ¡ Cortot Exercises five-finger-scale with 4th
finger pressed down
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Consensus
l The consensus of these studies is that skilled piano techniques are influenced by flexible hand span and wrist joint mobility that enable efficient hand-arm coordination rather than by the size or shape of the hand and arm.
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Kinematics of Piano Playing (Jerde et al, 2006)
• Covariation of the Metacarpal and Proximal Interphalangeal Joints
• Finger Individuation in Coordination of the Hand Motion
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Predictors l Hand Size:
a) hand length b) hand width c) composite finger length.
l Hand Mobility (span and ulnar deviation): a) composite finger span 1-3 b) composite finger span 2-4 c) composite finger span 3-5 d) composite finger span 1-5 e) ulnar deviation at the wrist
l Weight variables: a) hand weight b) arm weight c) hand-arm weight ratio
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Dependent variables (Performance Variables)
l Dynamic evenness (key velocity) l Articulation (Key note-on to note-off timing)
evenness l Tempo – consecutive notes-on timing (real time beats) l Fourth finger-sustain in task #7 l Error, defined by before and after touch and wrong
notes
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Pianists were Identified in four Classifications
l Artists n=9 l Graduate piano major students n=8 l Undergraduate piano major students n=5 l Injured pianists n=9
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Pianists l A total of 31 pianists l ages ranging from 18 to 50 l 16 male and 15 female l 9 artist-pianists who performed internationally l 8 graduate piano performance majors l 5 undergraduate piano majors l 9 trained pianists who were currently
experiencing pain or injury. l All were “skilled” (i.e., classically trained) pianists,
signed IRB Informed Consent Form. 16
Measuring Hand
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Equipment: AvantGrand Piano: YAMAHA AvantGrand N3 version, hybrid piano with electronic speakers highlights
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Eight piano tasks
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Statistical Analysis l Nominal variables (sex and classification) are described as
frequencies with mean values ± SD and compared using X2 analysis or Fischer’s exact test as appropriate.
l Hand biomechanics and performance variables are treated as ranked (described as medians and 25th-75th percentiles) and continuous measures.
l Group medians for all continuous measures (hand biomechanics and performance variables) were compared between classifications using a Mann-Whitney U test or Kruskal-Wallis test.
l Spearman rank correlation test was used to measure the strength of association between the predictors and the dependent variables.
l Linear regression models were created in order to identify independent variables that predict changes in performance variables. P value ≤ 0.05 was considered statistically significant.
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Hand Biomechanics Differences by Sex Table 1. Hand Biomechanics Differences by Sex
Hand length .0001 * Finger length .0011 * Hand width .0001 * Finger span 1-3 .0141 * Finger span 1-5 .0451 * Finger span 2-4 .7111 Finger span 3-5 .3181 Hand weight .0031 * Arm weight .0001 * Hand/arm weight ratio .2241
There were no significant Hand Biomechanics Differencdes by Pianist Classification
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Performance differences among pianist groups Three performance variables were found significantly different among the groups: l Articulation (duration from note-on to note off in legato
exercises in ms (p=0.026) l Playing speed (timing of consecutive notes-on in legato
in ms (p=0.019) l Playing speed (timing of consecutive notes-on in staccato
playing in ms (p=0.008)
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Evenness of Articulation and Tempo (Performance differences among pianist groups continued)
a) Evenness of articulation (SD note-on to note-off) in playing all legato exercises, artists and graduate students were not significantly different (p=0.96), while undergraduate and injured pianists showed significant differences (p=0.007 and p=0.05 respectively) from the previous two groups.
b) Evenness of tempo (SD consecutive notes-on) in all legato playing also showed significant differences between artist and graduate pianists and undergraduate and injured pianists (p=0.02 and p=0.02 respectively).
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Evenness of Articulation and Tempo(continued)
c) Evenness of tempo (SD consecutive notes-on) in all staccato playing showed significant differences among all four groups of pianists (comparison within groups all with p values less than 0.05).
d) No significant differences were found in key velocity (legato p=0.231, staccato p=0.466) or error (p=0.308) performance variables.
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Performance Differences (Evenness of Articulation and Tempo) among groups
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Correlations between performance variables and hand biomechanics: The fourth-finger sustain in playing Piano Task #7 and Hand
Fourth-finger sustain ¡ hand length .47 p=.012* ¡ hand width .387 p=.032* ¡ finger length .477 p=.007* ¡ finger span 1 to 3 .448 p=.011*
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Evenness of velocity (dynamic control) and Hand: Correlations between performance variables and hand biomechanics continued
l Significant positive correlations between the composite (all 8 tasks) evenness of velocity in legato playing and hand width and finger span fingers 1 to 5
l Significant positive correlations between the composite (all 8 tasks) evenness of velocity in staccato playing with hand width and finger span fingers 1 to 5, but also finger spans 1-3, 2-4, and 3-5
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Evenness of velocity in legato playing and Hand
Evenness of Velocity ¡ Hand width .37 p=.042* ¡ Finger span 1-5 .39 p=.028*
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Evenness of velocity in staccato playing and Hand
Evenness of Velocity ¡ Hand width .422 p=.042* ¡ Finger span 1-5 .539 p=.0001* ¡ Finger span 1-3 .459 p=.009* ¡ Finger span 2-4 .48 p=.006* ¡ Finger span 3-5 .483 p=.006*
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Positive Correlations between Hand Biomechanics and Performance Variables
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Prediction Model—Linear Regression
l For every 1 cm increase in finger span of fingers 1 to 5, the percentage of correct notes increased by 6% (B=0.057, p=0.037) and the percentage of fourth-finger sustain decreased by 10% (B=-0.103, p=0.003).
l For every 1 cm increased in finger span of fingers 1 to 3, the percentage of fourth-finger sustain was increase by 6% (B=0.059, p=0.005).
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Predictor Model Table
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Summary
l Sex Differences: hand sizes are significantly different between male and female except finger spans 2-4. 3-5. and ulnar deviation– this is consistent with the previous three studies.
l Pianists Classification: hand size factors show no difference among the pianists classes.
l Pianist classification does not show difference in key velocity control (loudness) or error rate.
l Pianist classification does show differences in evenness control in articulation and tempo.
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Summary continued
l Performance of task #7: hand length, hand width, finger lengths, finger span 1-3 were correlated with fourth-finger sustain.
l Key velocity evenness in legato playing: hand width and finger span fingers 1-5 were correlated with evenness of key velocity.
l Key velocity evenness in staccato playing: finger spans, 1-3, 2-4, and 3-5 were also positively correlated.
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Summary continued
l Finger spans 1-3 and 1-5 predicted two performance variables: ¡ Wide finger span 1-5 seem to allow pianists to find
correct notes easily. ¡ The same wide finger span 1-5 seem to hinder the
fourth-finger sustain, while finger span 1-3 seem to help fourth finger sustain in (#7).
¡ We will look at motion capture data to understand these regression results better.
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Statistical method l Small number purposive sampling l Our variables meet the required assumption for
of non-parametric Mann Whitney U8 and Kruskal-Wallis9 Tests as alternatives to T-test or ANOVA.
l Power of large number l Intensive nature & multiple individualized
measurements limit the number in the study. l Cumulative data 36
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Implications
l Pianists’ biomechanical profiles is useful for
¡ Efficient playing ¡ Injury preventive pedagogy ¡ Rehabilitation strategies
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Gary Graffman & Leon Fleisher
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Student 1
l Small 2-4 finger span (2.8 inches)
l Finger weakness contributed to injury
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Injured Pianists Examples
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Student 8
l Short fifth finger
Adult piano student
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Artist 6
l Large hand/arm weight ratio l Hand weight: 52 oz. l Arm weight: 87 oz. l Ratio: 0.60
Model artist pianist
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Jazz performer
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College piano instructor
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College piano instructor
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Healthy artist pianist
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“Playing”-‐-‐posture matters!!!
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Speaking of postureèfocal dystonia???