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Modification of upper limb performance with and without visual feedback in a patient with cerebral palsy: A case study
ESMAC 2012 abstract / Gait & Posture 38 (2013) S1–S116
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Discussion and conclusions: Despite the influence of MTS on biomechanics and physiology (tone reduction and improvements of joint mobility and gait pattern) MTS does not change abnormal patterns of muscle activation counter-intuitively. The findings of this study are of major clinical importance. Recurrence of increased muslce tone and deterioration of gait analysis as well as clinical parameters between E1 and E2 may be attributed to these persistent pathological activation patterns.
Reference [1] Vlachou M, et al. Acta Orthopaedica Belgica 2009;75:808–14.
Fig. 1. Mean SM (left) and mean JC (right) for adults and children during CW and CCW trials.
http://dx.doi.org/10.1016/j.gaitpost.2013.07.170
References
P79
[1] [2] [3] [4]
Differences between children and adults in upper limb motor control during the execution of typical robotic rehabilitation tasks Alessandra Pacilli 1,2 , Marco Germanotta 1,2 , Stefano Rossi 1,2 , Maurizio Petrarca 2 , Enrico Castelli 2 , Paolo Cappa 1,2 1
Sapienza“- University of Rome, Department of Mechanical and Aerospace Engineering, Rome, Italy 2 Bambino Gesù” Children’s Hospital, IRCCS, Movement Analysis and Robotic Laboratory (MARLab) - Pediatric Neuro-Rehabilitation Division, Rome, Italy Introduction: Robots for rehabilitation treatment are not only employed for the treatment and performance evaluation for stroke survivors, but also to assess in healthy subjects their adaptability to dynamic fields. In this context, few studies have investigated the age-related modifications of motor control strategies [1]. Although motor control differences between adults and children have been observed [2], in our knowledge no studies have quantified them during rehabilitative robot tasks. In order to achieve this goal, we decided to comparatively examine upper limb kinematics during circle drawing tasks in healthy adults and children; that choice is justified because the previously indicated task: (i) is widely used for patients evaluation, and (ii) it requires coordination of both the shoulder and elbow joints. Patients/materials and methods: Eight healthy, right children (age: 8.0 ± 1.0 years) and eight healthy, right adults (age: 24.5 ± 1.2 years) were asked to track 8 ClockWise (CW) and 8 CounterClockWise (CCW) circles (radius: 8 cm) in the horizontal workspace, with the InMotion Arm Robot device. An optoelectronic system (Vicon 512) was used to acquire kinematics for the upper limb and the trunk. As smoothness indicator, we used the Speed Metric (SM) [3] calculated as the mean of the speed divided by the peak speed; instead, the correlation between the elbow flexion angle and the abd-adduction shoulder angle, called Joint Correlation (JC) [4], was used to explore the synergies of the entire upper limb. Results: As shown in Fig. 1, the mean JC is not statistically significant different (p > 0.05) between adults and children, both in CW and CCW trials, while the SM index is always higher (p < 0.05) for the adults (SMCCW = 0.59 ± 0.06; SMCW = 0.63 ± 0.10) than for children (SMCCW = 0.40 ± 0.06; SMCW = 0.45 ± 0.06) Discussion and conclusions: The motor synergy of the upper limb is completely developed in children aged 8.0 ± 1.0, as results from the JC values; nevertheless, the lower values of the SM clearly show that children has not yet reached the typical young adults fine tuning of muscular movement.
Takahashi, et al. Journal of Neurophysiology 2003. Jansen-Osmann, et al. Experimental Brain Research 2002. Rohrer, et al. Journal of Neuroscience 2002. Dipietro, et al. Journal of Neurophysiology 2007.
http://dx.doi.org/10.1016/j.gaitpost.2013.07.171 P81 Modification of upper limb performance with and without visual feedback in a patient with cerebral palsy: A case study Marco Germanotta 1,2 , Alessandra Pacilli 1,2 , Stefano Rossi 1,2 , Maurizio Petrarca 2 , Enrico Castelli 2 , Paolo Cappa 1,2 1 “Sapienza” University of Rome, Department of Mechanical and Aerospace Engineering, Rome, Italy 2 Bambino Gesù” Children’s Hospital, IRCCS, Movement Analysis and Robotic Laboratory (MARLab) - Pediatric Neuro-Rehabilitation Division, Rome, Italy
Introduction: Cerebral palsy (CP) is one of the most common childhood disorders, with an incidence of 2–2.5 per 1000 living births [1]. With respect to motor impairments, disturbances in proprioception have been less studied [2]. However, it has been shown how activity limitations in children with CP are related not only with movement execution, but also with the planning of movement, which is strongly related to the proprioceptive system [3]. Therefore, this study aimed to compare motor performance of a hemiplegic child, in the presence and absence of visual feedback, with an age-matched healthy group. Patients/materials and methods: Five healthy subjects (8 ± 2 years old) and one patient with cerebral palsy (8 years old) were involved in the present study. They were asked to perform circle drawing tasks (8 cm diameter) with the planar robot InMotion Arm Robot (Interactive Motion Technologies, Inc., US). Specifically, they were asked to first draw three circles clockwise (CW) and three circles counterclockwise (CCW), while visual feedback was provided on a monitor (eyes open condition, EO); then, they were asked to perform the same movements blindfolded (eyes closed condition, EC). Performance was evaluated by means of two indexes: the ratio between the axis of the ellipse best fitting the hand path; and the ratio between the area of the performed ellipse and the area of the displayed circle. Results: In Fig. 1, the mean values of the two metrics (area ratio and axes ratio), with and without visual information, are reported for healthy subjects and the pathologic subject. Without visual feedback, axes ratio metric mean values are higher in the control group (>1) and smaller in the pathologic subject (<1). Otherwise,
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ESMAC 2012 abstract / Gait & Posture 38 (2013) S1–S116
Fig. 1. Mean values and SDs of area ratio (left) and axes ratio (right).
trend and mean values of axes ratio metric are similar in control group and in the child with CP, both in EO and EC. For both metrics, performance of the child with CP is worse in CCW than in CW direction. Healthy subjects, instead, seem to be not influenced by direction of movement. Discussion and conclusions: The area ratio index suggests that the child with CP perceives the space, in absence of a visual feedback, in a different way, compared with healthy subjects. In fact, the control group seems to underestimate it, while child with CP seems to overestimate it. The disease, however, does not appear to affect the ability to perform the requested task in EC, as shown by axes ratio index. Finally, the difference of both metrics in CW and CCW might be explained by an effect of lesion side on the planning of the movement. References [1] Lin. Journal of Neurology, Neurosurgery & Psychiatry 2003. [2] Goble DJ, et al. International Journal of Rehabilitation Research 2009. [3] Steenbergen B, et al. Developmental Medicine and Child Neurology 2006.
http://dx.doi.org/10.1016/j.gaitpost.2013.07.172 P83 The “arm posture score” for assessment of arm swing during gait: Evaluation of additional rotational components and different gait speeds Gunilla E. Frykberg, Gudrun Johansson, Helena Grip, Jonas Selling, Charlotte Häger Umeå University, Department of Community Medicine and Rehabilitation/Physiotherapy, Umeå, Sweden Introduction: Traditionally, focus in 3D gait analysis has been on the lower extremities with considerable less attention paid to the role of the arms and their movements. The Arm Posture Score (APS) was recently presented for assessment of arm swing in children with cerebral palsy [1]. This index is calculated from four arm movement variables (shoulder flex/ext; shoulder abd/add; elbow flex/ext; wrist flex/ext), and will from now on here be referred to as APS4 . A potential limitation of this arm score is that it does not include any rotational movements. The aims of the present study were, in healthy adults, firstly to investigate the effect on APS4 by adding two components of arm rotation (shoulder int/ext rot; forearm pro/sup), which results in an index referred to as APS6 , and secondly to determine the influence of gait speed on both APS4 and APS6 . Patients/materials and methods: Twenty-five healthy subjects (14 women, mean age 64 years ±13) have so far participated. Data collection was performed in a movement laboratory with 8 optoelectronic cameras (240 Hz, Oqus®, Qualisys, Gothenburg, Sweden) and 27 passive markers applied on anatomical landmarks and rigid clusters on the trunk and bilaterally to the upper extremities. The subjects walked 10 m on a walkway at self-selected speed (mean 1.35 m/s ±0.15). A subgroup of eleven subjects (6 women, mean
age 63 years ±13) walked at a slow speed (paced by a metronome, 0.68 m/s ±0.07) in addition to the self-selected speed. Six trials per subject were analysed. Calculations of gait variable scores (GVS, for each movement variable) and APS4 were performed according to Riad et al. [1] and in addition we calculated APS6 . The deviation of each movement variable from the value of the reference data, i.e. the whole group of participants, was calculated as the root mean square difference (RMSD) from normal. The APS score then equals the RMS-average of four or six GVS, respectively. The unit of APS is in degrees and a higher value implies a larger deviation from normal. The statistical analyses were performed with Wilcoxon signed rank tests and a level of p < 0.05 was considered significant. Results: Preliminary results demonstrate significantly higher APS6 values, as compared to APS4 , for both arms at self- selected walking speed (p < 0.001). When walking at a slow speed, the deviation from normal revealed significantly higher APS6 than APS4 values for the dominant arm (p = 0.006), while there was no significant difference for the non-dominant arm (p = 0.05). Both APS4 and APS6 showed significantly higher values regarding both arms, i.e. more deviating from normal, during slow walking as compared to the self-selected speed. Discussion and conclusions: Adding two rotational arm components to the earlier presented APS [1] resulted in significantly higher values on most APS6 variables, i.e. APS6 gives a higher value than APS4 . These results might imply that the two additional arm components provide relevant information of arm swing during gait in healthy subjects. A slower gait speed resulted in significantly higher APS4 as well as APS6 values indicating more deviant arm movements during slow walking. Thus, gait speed may need to be taken into account when quantifying arm swing during gait using 3D information. As this is an ongoing study where preliminary results are reported and merely in a small group of subjects there is a need for more data as well as a deeper scrutiny of the character of APS4 and APS6 for determination of its usefulness to describe arm movements during gait as well as to evaluate effects of intervention. Reference [1] Riad J, Coleman S, Lundh D, Broström E. Gait & Posture 2011;33(1):48–53.
http://dx.doi.org/10.1016/j.gaitpost.2013.07.173
S81
Discussion and conclusions: Despite the influence of MTS on biomechanics and physiology (tone reduction and improvements of joint mobility and gait pattern) MTS does not change abnormal patterns of muscle activation counter-intuitively. The findings of this study are of major clinical importance. Recurrence of increased muslce tone and deterioration of gait analysis as well as clinical parameters between E1 and E2 may be attributed to these persistent pathological activation patterns.
Reference [1] Vlachou M, et al. Acta Orthopaedica Belgica 2009;75:808–14.
Fig. 1. Mean SM (left) and mean JC (right) for adults and children during CW and CCW trials.
http://dx.doi.org/10.1016/j.gaitpost.2013.07.170
References
P79
[1] [2] [3] [4]
Differences between children and adults in upper limb motor control during the execution of typical robotic rehabilitation tasks Alessandra Pacilli 1,2 , Marco Germanotta 1,2 , Stefano Rossi 1,2 , Maurizio Petrarca 2 , Enrico Castelli 2 , Paolo Cappa 1,2 1
Sapienza“- University of Rome, Department of Mechanical and Aerospace Engineering, Rome, Italy 2 Bambino Gesù” Children’s Hospital, IRCCS, Movement Analysis and Robotic Laboratory (MARLab) - Pediatric Neuro-Rehabilitation Division, Rome, Italy Introduction: Robots for rehabilitation treatment are not only employed for the treatment and performance evaluation for stroke survivors, but also to assess in healthy subjects their adaptability to dynamic fields. In this context, few studies have investigated the age-related modifications of motor control strategies [1]. Although motor control differences between adults and children have been observed [2], in our knowledge no studies have quantified them during rehabilitative robot tasks. In order to achieve this goal, we decided to comparatively examine upper limb kinematics during circle drawing tasks in healthy adults and children; that choice is justified because the previously indicated task: (i) is widely used for patients evaluation, and (ii) it requires coordination of both the shoulder and elbow joints. Patients/materials and methods: Eight healthy, right children (age: 8.0 ± 1.0 years) and eight healthy, right adults (age: 24.5 ± 1.2 years) were asked to track 8 ClockWise (CW) and 8 CounterClockWise (CCW) circles (radius: 8 cm) in the horizontal workspace, with the InMotion Arm Robot device. An optoelectronic system (Vicon 512) was used to acquire kinematics for the upper limb and the trunk. As smoothness indicator, we used the Speed Metric (SM) [3] calculated as the mean of the speed divided by the peak speed; instead, the correlation between the elbow flexion angle and the abd-adduction shoulder angle, called Joint Correlation (JC) [4], was used to explore the synergies of the entire upper limb. Results: As shown in Fig. 1, the mean JC is not statistically significant different (p > 0.05) between adults and children, both in CW and CCW trials, while the SM index is always higher (p < 0.05) for the adults (SMCCW = 0.59 ± 0.06; SMCW = 0.63 ± 0.10) than for children (SMCCW = 0.40 ± 0.06; SMCW = 0.45 ± 0.06) Discussion and conclusions: The motor synergy of the upper limb is completely developed in children aged 8.0 ± 1.0, as results from the JC values; nevertheless, the lower values of the SM clearly show that children has not yet reached the typical young adults fine tuning of muscular movement.
Takahashi, et al. Journal of Neurophysiology 2003. Jansen-Osmann, et al. Experimental Brain Research 2002. Rohrer, et al. Journal of Neuroscience 2002. Dipietro, et al. Journal of Neurophysiology 2007.
http://dx.doi.org/10.1016/j.gaitpost.2013.07.171 P81 Modification of upper limb performance with and without visual feedback in a patient with cerebral palsy: A case study Marco Germanotta 1,2 , Alessandra Pacilli 1,2 , Stefano Rossi 1,2 , Maurizio Petrarca 2 , Enrico Castelli 2 , Paolo Cappa 1,2 1 “Sapienza” University of Rome, Department of Mechanical and Aerospace Engineering, Rome, Italy 2 Bambino Gesù” Children’s Hospital, IRCCS, Movement Analysis and Robotic Laboratory (MARLab) - Pediatric Neuro-Rehabilitation Division, Rome, Italy
Introduction: Cerebral palsy (CP) is one of the most common childhood disorders, with an incidence of 2–2.5 per 1000 living births [1]. With respect to motor impairments, disturbances in proprioception have been less studied [2]. However, it has been shown how activity limitations in children with CP are related not only with movement execution, but also with the planning of movement, which is strongly related to the proprioceptive system [3]. Therefore, this study aimed to compare motor performance of a hemiplegic child, in the presence and absence of visual feedback, with an age-matched healthy group. Patients/materials and methods: Five healthy subjects (8 ± 2 years old) and one patient with cerebral palsy (8 years old) were involved in the present study. They were asked to perform circle drawing tasks (8 cm diameter) with the planar robot InMotion Arm Robot (Interactive Motion Technologies, Inc., US). Specifically, they were asked to first draw three circles clockwise (CW) and three circles counterclockwise (CCW), while visual feedback was provided on a monitor (eyes open condition, EO); then, they were asked to perform the same movements blindfolded (eyes closed condition, EC). Performance was evaluated by means of two indexes: the ratio between the axis of the ellipse best fitting the hand path; and the ratio between the area of the performed ellipse and the area of the displayed circle. Results: In Fig. 1, the mean values of the two metrics (area ratio and axes ratio), with and without visual information, are reported for healthy subjects and the pathologic subject. Without visual feedback, axes ratio metric mean values are higher in the control group (>1) and smaller in the pathologic subject (<1). Otherwise,
S82
ESMAC 2012 abstract / Gait & Posture 38 (2013) S1–S116
Fig. 1. Mean values and SDs of area ratio (left) and axes ratio (right).
trend and mean values of axes ratio metric are similar in control group and in the child with CP, both in EO and EC. For both metrics, performance of the child with CP is worse in CCW than in CW direction. Healthy subjects, instead, seem to be not influenced by direction of movement. Discussion and conclusions: The area ratio index suggests that the child with CP perceives the space, in absence of a visual feedback, in a different way, compared with healthy subjects. In fact, the control group seems to underestimate it, while child with CP seems to overestimate it. The disease, however, does not appear to affect the ability to perform the requested task in EC, as shown by axes ratio index. Finally, the difference of both metrics in CW and CCW might be explained by an effect of lesion side on the planning of the movement. References [1] Lin. Journal of Neurology, Neurosurgery & Psychiatry 2003. [2] Goble DJ, et al. International Journal of Rehabilitation Research 2009. [3] Steenbergen B, et al. Developmental Medicine and Child Neurology 2006.
http://dx.doi.org/10.1016/j.gaitpost.2013.07.172 P83 The “arm posture score” for assessment of arm swing during gait: Evaluation of additional rotational components and different gait speeds Gunilla E. Frykberg, Gudrun Johansson, Helena Grip, Jonas Selling, Charlotte Häger Umeå University, Department of Community Medicine and Rehabilitation/Physiotherapy, Umeå, Sweden Introduction: Traditionally, focus in 3D gait analysis has been on the lower extremities with considerable less attention paid to the role of the arms and their movements. The Arm Posture Score (APS) was recently presented for assessment of arm swing in children with cerebral palsy [1]. This index is calculated from four arm movement variables (shoulder flex/ext; shoulder abd/add; elbow flex/ext; wrist flex/ext), and will from now on here be referred to as APS4 . A potential limitation of this arm score is that it does not include any rotational movements. The aims of the present study were, in healthy adults, firstly to investigate the effect on APS4 by adding two components of arm rotation (shoulder int/ext rot; forearm pro/sup), which results in an index referred to as APS6 , and secondly to determine the influence of gait speed on both APS4 and APS6 . Patients/materials and methods: Twenty-five healthy subjects (14 women, mean age 64 years ±13) have so far participated. Data collection was performed in a movement laboratory with 8 optoelectronic cameras (240 Hz, Oqus®, Qualisys, Gothenburg, Sweden) and 27 passive markers applied on anatomical landmarks and rigid clusters on the trunk and bilaterally to the upper extremities. The subjects walked 10 m on a walkway at self-selected speed (mean 1.35 m/s ±0.15). A subgroup of eleven subjects (6 women, mean
age 63 years ±13) walked at a slow speed (paced by a metronome, 0.68 m/s ±0.07) in addition to the self-selected speed. Six trials per subject were analysed. Calculations of gait variable scores (GVS, for each movement variable) and APS4 were performed according to Riad et al. [1] and in addition we calculated APS6 . The deviation of each movement variable from the value of the reference data, i.e. the whole group of participants, was calculated as the root mean square difference (RMSD) from normal. The APS score then equals the RMS-average of four or six GVS, respectively. The unit of APS is in degrees and a higher value implies a larger deviation from normal. The statistical analyses were performed with Wilcoxon signed rank tests and a level of p < 0.05 was considered significant. Results: Preliminary results demonstrate significantly higher APS6 values, as compared to APS4 , for both arms at self- selected walking speed (p < 0.001). When walking at a slow speed, the deviation from normal revealed significantly higher APS6 than APS4 values for the dominant arm (p = 0.006), while there was no significant difference for the non-dominant arm (p = 0.05). Both APS4 and APS6 showed significantly higher values regarding both arms, i.e. more deviating from normal, during slow walking as compared to the self-selected speed. Discussion and conclusions: Adding two rotational arm components to the earlier presented APS [1] resulted in significantly higher values on most APS6 variables, i.e. APS6 gives a higher value than APS4 . These results might imply that the two additional arm components provide relevant information of arm swing during gait in healthy subjects. A slower gait speed resulted in significantly higher APS4 as well as APS6 values indicating more deviant arm movements during slow walking. Thus, gait speed may need to be taken into account when quantifying arm swing during gait using 3D information. As this is an ongoing study where preliminary results are reported and merely in a small group of subjects there is a need for more data as well as a deeper scrutiny of the character of APS4 and APS6 for determination of its usefulness to describe arm movements during gait as well as to evaluate effects of intervention. Reference [1] Riad J, Coleman S, Lundh D, Broström E. Gait & Posture 2011;33(1):48–53.
http://dx.doi.org/10.1016/j.gaitpost.2013.07.173