Results for the aesthetic preference experiment.

<p>Twelve naïve volunteers (without significant experience of performing or attending dance) viewed all possible pairings of stick figures/ polygons for each body position, and judged which image they preferred. A preference coefficient for each stick figure/ shape was then computed by averaging preferences across participants. This was defined as the probability of each figure or shape being preferred to all the other figures or shapes representing the same body position. Linear regression was applied to relate preference of each figure or shape to the year of the production from which each original image was selected. r and p values for the two analyses are given.</p

Description of the positions included in the study: it should be noted that these postures, firstly established by Marius Petipa for The Sleeping Beauty in 1890, are fixed moments in the choreography and have been performed in identical form for over a century.

1<p><i>Number of repetitions of the same pose by the dancer in one production.</i></p>2<p><i>The ballet lasts approximately 6 min; timing is given with respect to the beginning of the first movement.</i></p>3<p><i>The ballet lasts approximately 1 min; timing is given with respect to the beginning of the first movement.</i></p

Three representative examples of the body positions analysed.

<p><u>Panel A: A highly skilled, unsupported position</u>. The leg elevation that the dancer can achieve depends on her flexibility and her ability to simultaneously maintain balance; <u>Panel B: A highly skilled, supported position</u>. Balance is made easier by the male dancer's support, and leg elevation depends largely on flexibility; <u>Panel C: A less skilled, unsupported position</u>. The leg elevation required by the choreography is less demanding compared to the posture in panel A and balance is less critical, as the position should be maintained only for a brief time. In each panel: right side - correlation between year (x-axis) and degree of leg elevation (y-axis), r = Pearson correlation coefficient; left side - upper row, archive material showing the positions where the angle was recorded; lower row: stick figures showing the mean angle for the corresponding year. The angles measured from these illustrative images appear as red dots along the corresponding regression line.</p

Correlation analyses for leg elevation and trunk inclination angles vs. year.

1<p>Angular values for the analysed positions were averaged across judges prior to analyses; r = Pearson correlation coefficient; N = number of images available.</p>2<p>HS = Highly Skilled postures: postures highly demanding in terms of balance (i.e. the ballerina is not supported by the male dancer) and/or motor constraints (i.e. leg elevation above 90–120 deg).</p>3<p>see an example in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0005023#pone-0005023-g001" target="_blank">Figure 1 A</a>.</p>4<p>see an example in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0005023#pone-0005023-g001" target="_blank">Figure 1B</a>.</p>5<p>LS = Less-skilled postures: postures less demanding in terms of balance (i.e. the ballerina is supported by the male dancer) and/or motor constraints (i.e. leg elevation below 90–120 deg).</p>6<p>see an example in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0005023#pone-0005023-g001" target="_blank">Figure 1C</a>.</p

Amplitude of leg elevation angles for the positions included in the study.

1<p>Mean values (averaged across the three judges).</p>2<p>standard deviations are reported for the material analysed for each year of the ballet production. Please refer to <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0005023#pone-0005023-t001" target="_blank">Table 1</a> for the number of entries computed for each position.</p

On the left, RMS of the acceleration components at the three levels.

<p>On the right, attenuation coefficients from pelvis to head (C_PH), from pelvis to sternum (C_PS), and from sternum to head (C_SH) along the three anatomical axes. Parameters computed for the TD and CP groups are represented with empty and filled box-plots, respectively. Significant between-groups differences (p < 0.05 or p < 0.01) are reported with the symbol § or §§, respectively.</p

Gait parameters obtained for both the TD and CP groups.

<p>Gait parameters obtained for both the TD and CP groups.</p

The role of feedback in the robotic-assisted upper limb rehabilitation in people with multiple sclerosis: a systematic review

Robotic-assisted upper limb rehabilitation might improve upper limb recovery in people with multiple sclerosis (PwMS) with moderate-to-severe disability. In the few existing studies, the training effects have been related to the type of intervention, if intensive, repetitive, or task-oriented training might promote neuroplasticity and recovery. Notably, most of these devices operate within a serious game context providing different feedback. Since feedback is a key component of motor control and thus involved in motor and cognitive rehabilitation, clinicians cannot desist from considering the potential contribution of feedback in the upper limb robot-assisted rehabilitation effects. In this systematic review, we reported the rehabilitation protocols used in the robot-assisted upper limb training in PwMS to provide state-of-the-art on the role of feedback in robotic-assisted Upper Limb rehabilitation. PubMed, the Cochrane Library, and the Physiotherapy Evidence Database databases were systematically searched from inception to March 2022. After a literature search, the classification systems for feedback and the serious game were applied. There is a need for sharing standard definitions and components of feedback and serious game in technologically assisted upper limb rehabilitation. Indeed, improving these aspects might further improve the effectiveness of such training in the management of PwMS.</p

Sensor location and axes orientation of the Magneto-Inertial Measurement Units (MIMUs) attached on the children’s body segments.

<p>H: head level; S: sternum level; P: pelvis.</p

RMS_a inter-component relationships for the two groups (TD in light grey and CP in black).

<p>The inter-component comparison graphs characterized by significant different regression lines between the TD and CP groups are reported in figure: RMS_aAP vs RMS_aML for head (p = 0.007), RMS_aML vs RMSaCC for sternum (p = 0.048), and RMS_aAP vs RMSaCC for pelvis (p = 0.043).</p