- Email: [email protected]
Measuring fluency: Comparison of impaired and unimpaired groups
S40
Abstracts / Gait & Posture 39S (2014) S1–S141
an appropriate measurement system to detect surgery dependent changes in reverse total shoulder arthoplasty. Keywords: Reverse shoulder arthroplasty; Outcome; Cuff tear arthropathy; 3D video analysis; Marker based system; Upper extremity; Biomechanic model http://dx.doi.org/10.1016/j.gaitpost.2014.04.056 052
Keynote 1: James Robb Scott’s parabola: Orthopaedic surgery and research in cerebral palsy: Best paper session 1
Muscle synergy complexity is related to selective motor control in cerebral palsy Michael H. Schwartz 1,2,∗ , Adam Rozumalski 1 , Katherine M. Steele 3 1
Gillette Children’s Specialty Healthcare, St. Paul, USA 2 University of Minnesota, Minneapolis, USA 3 Mechanical Engineering, University of Washington, Seattle, USA Introduction and aim: One theory for how humans control movement is that muscles are actuated in weighted groups called “synergies” [1]. Synergies are theorized to provide a simplified neuromuscular control strategy compared to controlling each muscle individually. Recent studies have found that synergies are altered after stroke, and that the structure of synergies is related to severity and time after injury [2,3]. Synergies have not been previously investigated in individuals with cerebral palsy (CP). Quantifying changes in synergies among individuals with CP can further our understanding of neurological pathology, and lead to improvements in treatment strategies. If synergies are reflective of neuromuscular control, then we would expect them to be related to severity of impaired control for individuals with CP. Patients/materials and methods: Electromyography (EMG) data was extracted for subjects who had undergone motion analysis at a single center prior to February 2013. Subjects had a primary diagnosis of CP, and surface EMG of the rectus femoris, medial and lateral hamstrings, gastrocnemius, and anterior tibialis were monitored while each subject walked at their self-selected speed (Nsubjects = 532, Ntrials = 3614). The EMG data were decomposed using nonnegative matrix factorization to determine the relative weighting of muscles in each synergy, and the activation of each synergy over the gait cycle [4]. Solutions based on 1, 2, 3, and 4 synergies were found, and the variance accounted for (VAF) for each solution was calculated. Results were compared to a group of 83 typically developing children who had previously undergone motion analysis at the same center. Selective motor control (patterned, partially isolated, completely isolated) was measured at 16 levels using standard clinical examination methods, then converted to a single overall selective motor control index using principal component analysis [5]. We hypothesized that fewer synergies would be required to describe muscle activity during gait in individuals with CP, and that the VAF for a given number of synergies would increase with worsening selective motor control; suggesting a simplified control strategy. Results: Children with CP required fewer synergies to describe the variance in EMG activity compared to typically developing children (Fig. 1). In 63% of typically developing children, 3 or more synergies were needed to describe 90% of the variance in EMG data. In contrast, in 88% of children with CP, only 1 or 2 synergies were required to reach the same VAF. The VAF increased progressively
Fig. 1. Mean variance accounted for (VAF) by 1–4 synergies for typically developing children and children with CP. The VAF for every number of synergies increased with worsening selective motor control.
with severity for each of the synergy reconstructions. For example, one synergy described 75% of the VAF for typically developing individuals compared to 88% for individuals with completely patterned motor control. Discussion and conclusions: Children with CP utilized fewer synergies during gait than typically developing children; similar to previous studies of synergies after stroke. These results suggest that individuals with CP use a simpler neuromuscular control strategy during gait compared to unimpaired individuals. Measures of synergies during gait and other activities may provide a new quantitative measure of motor control that can be used to develop rehabilitation strategies or evaluate the impact of treatment for individuals with CP. Reference [1] [2] [3] [4] [5]
Lee WA. J Mot Behav 1984;16:135–70. Clark DJ, et al. J Neurophys 2010;103:844–57. Cheung V, et al. PNAS 2012;108:14652–6. Tresch MC, et al. J Neurophys 2006;95:2199–212. Rozumalski A, et al. Gait Posture 2009;30:155–60.
http://dx.doi.org/10.1016/j.gaitpost.2014.04.057 053 Measuring fluency: Comparison of impaired and unimpaired groups A. Kerr 1,∗ , D. Rafferty 2 , P. Dall 2 , P. Rowe 1 , V. Pomeroy 3 1
University of Strathclyde, United Kingdom Glasgow Caledonian University, United Kingdom 3 University of East Anglia, United Kingdom 2
Introduction and aim: Fluent movement (smooth, coordinated, unhesitating) is the visible output of a mature intact neuromusculoskeletal system and consequently a key part of the assessment and treatment of neurological conditions[1]. Despite its value, movement fluency has only been measured subjectively by therapists. The field of therapy robots has led to objective definitions of variables such as co-ordination and smoothness which can be more widely applied. Our primary aim was to develop clinically meaningful objective definitions of movement fluency and bench test them across impaired and unimpaired populations.
Abstracts / Gait & Posture 39S (2014) S1–S141
S41
Table 1 Mean and SD of fluency measurements. Participants
Task
Smoothness
Co-ordination
Hesitation
Young (n = 20) Old (n = 18) Fallers (n = 18) Stroke pre-rehab (n = 10) Stroke: post-rehab (n = 10)
STW STW STW STS STS
18.25(2.2) 42.50(11.4) 44.25(7.3) 143.4(66.0) 88.6(68.6)
13.16%(6.6) 11.33%(13.0) 1.47%(9.9) 4.48%(3.9) 13.82%(7.9)
20.82%(11.4) 30.29%(15.9) 47.51%(18.0) 19.32%(10.5) 40.88%(20.8)
Patients/materials and methods: Three dimensional trajectory data were extracted from two trials; (1) a biomechanical analysis of the sit to walk [STW] movement in older adults [2] and (2) the sit to stand [STS] tests from a stroke rehabilitation trial [3]. Both studies had ethical approval. This dataset comprised four participant groups; (1) stroke survivors, pre and post rehabilitation, n = 10, age 64.1 ± 11.1), (2) young adults (n = 20, age 33.1 ± 8.0), (3) old adults (n = 18, age 70.3 ± 5.0), and (4) old adults at risk of falling (OARF) (n = 18, age 79.6 ± 7.5). Trajectory data were collected at 50 Hz, filtered [low-pass 4th order Butterworth, cut-off 6 Hz] and interpolated [non-uniform rational B-spline, max gap fill ten frames]. A model of the body was then constructed and joint angles and total body centre of mass [CoM] calculated. Onset time (first continuous forward movement of the CoM) and end time (peak height of CoM for the STS movement and end of first swing phase for the STW movement) were recorded for each movement. Finally three fluency variables were derived: (1) Hesitation during movement: For the STW movement this was the percentage drop in forward velocity of CoM, for STS it was the overlap [percentage of total movement time] between the end of forward CoM velocity and start of vertical velocity; smaller overlaps indicating more hesitant movement, (2) Co-ordination: The temporal overlap [percentage of total movement time] between the end of hip flexion and start of knee extension and 3) Smoothness: Number of inflections in the CoM jerk signal [4]. These variables were statistically compared across the groups for either movement. Results: All three fluency measures varied significantly across the groups (see Table 1). Hesitation during the STW movement was greatest (F = 15.11, p < 0.001) in the OARF group compared to old and younger adults. Co-ordination was lowest (F = 44.88, p < 0.001) in the OARF compared to both the young and old. Smoothness was best (F = 35.96, p < 0.001) in the younger adults compared to the old and OARF. For stroke survivors the STS movement became less hesitant (F = 6.01, p = 0.031) smoother (F = 3.22, p = 0.085) and more co-ordinated (F = 9.36, p = 0.007) after rehabilitation. Discussion and conclusions: This study found significant differences in movement fluency across groups with and without impaired mobility and demonstrated changes in fluency following rehabilitation. The discriminant validity and sensitivity to change of these novel measures of human movement support their use as objective measures of fluency and will allow greater scrutiny of the effectiveness of rehabilitation interventions as well as shaping future interventions. Reference [1] Davidson. Physiotherapists working with stroke patients: a national 348 survey. Physiotherapy 2000:86. [2] Kerr, et al. Defining phases for the sit-to-walk movement. Clin Biomech 2007;19:385–90. [3] Cooke, et al. Efficacy of functional strength training. Neurorehabil Neural Repair 2010;24:88. [4] Rohrer, et al. Movement smoothness changes during stroke recovery. J Neurosci 2002;22:8297–304.
http://dx.doi.org/10.1016/j.gaitpost.2014.04.058
Fig. 1. Mean and standard deviations between GCSH (grey) and RCH (black) Ankle Dorsiflexion normative reference data.
054 The comparison of normative reference data from different gait analysis services Ornella Pinzone 1,∗ , Richard Baker 1 , Michael H. Schwartz 2,3 1
University of Salford, UK Gillette Children’s Specialty Healthcare, St. Paul, MN, USA 3 University of Minnesota, Minneapolis, MN, USA 2
E-mail address: [email protected] (O. Pinzone). 1. INTRODUCTION and AIM Introduction and aim: In the past it has been considered acceptable for gait analysis services to vary in their data capture protocols and the purpose of collecting reference datasets was to allow for these differences between laboratories. As the discipline matures there is a growing requirement for standardization between services. The rationale for collecting reference datasets in the future should thus be to harmonize protocols through comparison between different services. This study provides a mechanism to compare normative reference datasets between services and hence develops a conceptual basis for programs to harmonize data capture protocols nationally and internationally. Patients/materials and methods: Means and standard deviations of the clinically important kinematic and kinetics variables from two gait analysis services (Gillette Children’s Specialty Healthcare, GCSH [n = 81], and the Royal Children’s Hospital, Melbourne, RCH [n = 31]) were over-plotted to visualize the level of agreement (Fig. 1). The mean trace for each center separately was compared to the un-weighted mean trace for the two services. The root mean square difference (RMS) for each variable over the gait cycle indicates systematic differences from the overall mean. The mean difference (mean) indicates differences in offsets and the standard deviation (SD) indicates differences in waveform. (Note that
Abstracts / Gait & Posture 39S (2014) S1–S141
an appropriate measurement system to detect surgery dependent changes in reverse total shoulder arthoplasty. Keywords: Reverse shoulder arthroplasty; Outcome; Cuff tear arthropathy; 3D video analysis; Marker based system; Upper extremity; Biomechanic model http://dx.doi.org/10.1016/j.gaitpost.2014.04.056 052
Keynote 1: James Robb Scott’s parabola: Orthopaedic surgery and research in cerebral palsy: Best paper session 1
Muscle synergy complexity is related to selective motor control in cerebral palsy Michael H. Schwartz 1,2,∗ , Adam Rozumalski 1 , Katherine M. Steele 3 1
Gillette Children’s Specialty Healthcare, St. Paul, USA 2 University of Minnesota, Minneapolis, USA 3 Mechanical Engineering, University of Washington, Seattle, USA Introduction and aim: One theory for how humans control movement is that muscles are actuated in weighted groups called “synergies” [1]. Synergies are theorized to provide a simplified neuromuscular control strategy compared to controlling each muscle individually. Recent studies have found that synergies are altered after stroke, and that the structure of synergies is related to severity and time after injury [2,3]. Synergies have not been previously investigated in individuals with cerebral palsy (CP). Quantifying changes in synergies among individuals with CP can further our understanding of neurological pathology, and lead to improvements in treatment strategies. If synergies are reflective of neuromuscular control, then we would expect them to be related to severity of impaired control for individuals with CP. Patients/materials and methods: Electromyography (EMG) data was extracted for subjects who had undergone motion analysis at a single center prior to February 2013. Subjects had a primary diagnosis of CP, and surface EMG of the rectus femoris, medial and lateral hamstrings, gastrocnemius, and anterior tibialis were monitored while each subject walked at their self-selected speed (Nsubjects = 532, Ntrials = 3614). The EMG data were decomposed using nonnegative matrix factorization to determine the relative weighting of muscles in each synergy, and the activation of each synergy over the gait cycle [4]. Solutions based on 1, 2, 3, and 4 synergies were found, and the variance accounted for (VAF) for each solution was calculated. Results were compared to a group of 83 typically developing children who had previously undergone motion analysis at the same center. Selective motor control (patterned, partially isolated, completely isolated) was measured at 16 levels using standard clinical examination methods, then converted to a single overall selective motor control index using principal component analysis [5]. We hypothesized that fewer synergies would be required to describe muscle activity during gait in individuals with CP, and that the VAF for a given number of synergies would increase with worsening selective motor control; suggesting a simplified control strategy. Results: Children with CP required fewer synergies to describe the variance in EMG activity compared to typically developing children (Fig. 1). In 63% of typically developing children, 3 or more synergies were needed to describe 90% of the variance in EMG data. In contrast, in 88% of children with CP, only 1 or 2 synergies were required to reach the same VAF. The VAF increased progressively
Fig. 1. Mean variance accounted for (VAF) by 1–4 synergies for typically developing children and children with CP. The VAF for every number of synergies increased with worsening selective motor control.
with severity for each of the synergy reconstructions. For example, one synergy described 75% of the VAF for typically developing individuals compared to 88% for individuals with completely patterned motor control. Discussion and conclusions: Children with CP utilized fewer synergies during gait than typically developing children; similar to previous studies of synergies after stroke. These results suggest that individuals with CP use a simpler neuromuscular control strategy during gait compared to unimpaired individuals. Measures of synergies during gait and other activities may provide a new quantitative measure of motor control that can be used to develop rehabilitation strategies or evaluate the impact of treatment for individuals with CP. Reference [1] [2] [3] [4] [5]
Lee WA. J Mot Behav 1984;16:135–70. Clark DJ, et al. J Neurophys 2010;103:844–57. Cheung V, et al. PNAS 2012;108:14652–6. Tresch MC, et al. J Neurophys 2006;95:2199–212. Rozumalski A, et al. Gait Posture 2009;30:155–60.
http://dx.doi.org/10.1016/j.gaitpost.2014.04.057 053 Measuring fluency: Comparison of impaired and unimpaired groups A. Kerr 1,∗ , D. Rafferty 2 , P. Dall 2 , P. Rowe 1 , V. Pomeroy 3 1
University of Strathclyde, United Kingdom Glasgow Caledonian University, United Kingdom 3 University of East Anglia, United Kingdom 2
Introduction and aim: Fluent movement (smooth, coordinated, unhesitating) is the visible output of a mature intact neuromusculoskeletal system and consequently a key part of the assessment and treatment of neurological conditions[1]. Despite its value, movement fluency has only been measured subjectively by therapists. The field of therapy robots has led to objective definitions of variables such as co-ordination and smoothness which can be more widely applied. Our primary aim was to develop clinically meaningful objective definitions of movement fluency and bench test them across impaired and unimpaired populations.
Abstracts / Gait & Posture 39S (2014) S1–S141
S41
Table 1 Mean and SD of fluency measurements. Participants
Task
Smoothness
Co-ordination
Hesitation
Young (n = 20) Old (n = 18) Fallers (n = 18) Stroke pre-rehab (n = 10) Stroke: post-rehab (n = 10)
STW STW STW STS STS
18.25(2.2) 42.50(11.4) 44.25(7.3) 143.4(66.0) 88.6(68.6)
13.16%(6.6) 11.33%(13.0) 1.47%(9.9) 4.48%(3.9) 13.82%(7.9)
20.82%(11.4) 30.29%(15.9) 47.51%(18.0) 19.32%(10.5) 40.88%(20.8)
Patients/materials and methods: Three dimensional trajectory data were extracted from two trials; (1) a biomechanical analysis of the sit to walk [STW] movement in older adults [2] and (2) the sit to stand [STS] tests from a stroke rehabilitation trial [3]. Both studies had ethical approval. This dataset comprised four participant groups; (1) stroke survivors, pre and post rehabilitation, n = 10, age 64.1 ± 11.1), (2) young adults (n = 20, age 33.1 ± 8.0), (3) old adults (n = 18, age 70.3 ± 5.0), and (4) old adults at risk of falling (OARF) (n = 18, age 79.6 ± 7.5). Trajectory data were collected at 50 Hz, filtered [low-pass 4th order Butterworth, cut-off 6 Hz] and interpolated [non-uniform rational B-spline, max gap fill ten frames]. A model of the body was then constructed and joint angles and total body centre of mass [CoM] calculated. Onset time (first continuous forward movement of the CoM) and end time (peak height of CoM for the STS movement and end of first swing phase for the STW movement) were recorded for each movement. Finally three fluency variables were derived: (1) Hesitation during movement: For the STW movement this was the percentage drop in forward velocity of CoM, for STS it was the overlap [percentage of total movement time] between the end of forward CoM velocity and start of vertical velocity; smaller overlaps indicating more hesitant movement, (2) Co-ordination: The temporal overlap [percentage of total movement time] between the end of hip flexion and start of knee extension and 3) Smoothness: Number of inflections in the CoM jerk signal [4]. These variables were statistically compared across the groups for either movement. Results: All three fluency measures varied significantly across the groups (see Table 1). Hesitation during the STW movement was greatest (F = 15.11, p < 0.001) in the OARF group compared to old and younger adults. Co-ordination was lowest (F = 44.88, p < 0.001) in the OARF compared to both the young and old. Smoothness was best (F = 35.96, p < 0.001) in the younger adults compared to the old and OARF. For stroke survivors the STS movement became less hesitant (F = 6.01, p = 0.031) smoother (F = 3.22, p = 0.085) and more co-ordinated (F = 9.36, p = 0.007) after rehabilitation. Discussion and conclusions: This study found significant differences in movement fluency across groups with and without impaired mobility and demonstrated changes in fluency following rehabilitation. The discriminant validity and sensitivity to change of these novel measures of human movement support their use as objective measures of fluency and will allow greater scrutiny of the effectiveness of rehabilitation interventions as well as shaping future interventions. Reference [1] Davidson. Physiotherapists working with stroke patients: a national 348 survey. Physiotherapy 2000:86. [2] Kerr, et al. Defining phases for the sit-to-walk movement. Clin Biomech 2007;19:385–90. [3] Cooke, et al. Efficacy of functional strength training. Neurorehabil Neural Repair 2010;24:88. [4] Rohrer, et al. Movement smoothness changes during stroke recovery. J Neurosci 2002;22:8297–304.
http://dx.doi.org/10.1016/j.gaitpost.2014.04.058
Fig. 1. Mean and standard deviations between GCSH (grey) and RCH (black) Ankle Dorsiflexion normative reference data.
054 The comparison of normative reference data from different gait analysis services Ornella Pinzone 1,∗ , Richard Baker 1 , Michael H. Schwartz 2,3 1
University of Salford, UK Gillette Children’s Specialty Healthcare, St. Paul, MN, USA 3 University of Minnesota, Minneapolis, MN, USA 2
E-mail address: [email protected] (O. Pinzone). 1. INTRODUCTION and AIM Introduction and aim: In the past it has been considered acceptable for gait analysis services to vary in their data capture protocols and the purpose of collecting reference datasets was to allow for these differences between laboratories. As the discipline matures there is a growing requirement for standardization between services. The rationale for collecting reference datasets in the future should thus be to harmonize protocols through comparison between different services. This study provides a mechanism to compare normative reference datasets between services and hence develops a conceptual basis for programs to harmonize data capture protocols nationally and internationally. Patients/materials and methods: Means and standard deviations of the clinically important kinematic and kinetics variables from two gait analysis services (Gillette Children’s Specialty Healthcare, GCSH [n = 81], and the Royal Children’s Hospital, Melbourne, RCH [n = 31]) were over-plotted to visualize the level of agreement (Fig. 1). The mean trace for each center separately was compared to the un-weighted mean trace for the two services. The root mean square difference (RMS) for each variable over the gait cycle indicates systematic differences from the overall mean. The mean difference (mean) indicates differences in offsets and the standard deviation (SD) indicates differences in waveform. (Note that