How is your doctor and therapist OBJECTIVELY determining your gait problems?
Or are they as bad as one of my PTs who gave me no feedback on what was wrong. But did demonstrate walking and tell me to; 'Walk this way'. WHAT FUCKING STUPIDITY WAS THAT? If I could 'walk that way' I wouldn't be here supposedly getting expert advice on how to correct my gait.
Are these in your hospital?
The latest here:
Computerised Dynography in Hemiparesis: Case study
Satralkar AN, Khatri SM, Anap DB, Shalini Sumbh
College of Physiotherapy, Pravara Institute of Medical Sciences (PIMS), Loni, Maharashtra State, India - 413736
Abstract
The purpose of this study was to assess the gait asymmetries in terms of temporal and force gait parametersusing Computer Dynography (CDG) system in a hemiparetic person. A 72 year male patient diagnosed as right sided cerebrovascular accident was referred to physiotherapy department with complaints of weakness in left upper & lower limbs and difficulty in walking in terms of impaired foot clearance since one and half year. His computerised gait dynography was done with Computer DynoGraphy (CDG)® system (Infotronic,Netherlands, http://www.infotronic.nl).It was found that there was asymmetry in his cyclogram,gait line, histogram, force gait line, force graphic, step times which included gait cycle, frequency, symmetry ratio, single support time, double support time, single swing, stance time and step time. Hence, it was concluded that CDG may be considered as one of the useful clinical tool for the assessment of gait asymmetries in hemiparetic patient so as to plan therapeutic interventions.
Key Words
Computer dynography, cyclogram, force graphics,histogram & hemiparesis.
Introduction
Stroke is considered to be a leading cause of disability throughout the world.1 The reported annual incidence of stroke in India is around 130 per one lakh population with an equal gender ratio. Further, it has been estimated that about 20 percent of patients with heart ailments are susceptible to stroke.2 After an initial period of high mortality, survival from stroke is generally good, with 50% of stroke patients alive for 7 years post stroke.3,4 Although, neurological impairments may resolve spontaneously or decrease following rehabilitation, persisting disabilities leading to partial or total dependence in activity of daily life (ADL) can still be present in 30 to 60 % of stroke survivors. More than 85%of stroke survivors can eventually walk with or without assistance.1, 5 Common features of walking after stroke include decreased gait velocity and asymmetrical gait pattern.6-7 It is suggested that in stroke patients, almost 40% of the required muscle work is performed by the muscles of the affected side during walking.8 Hip flexors, knee extensors and ankle plantarflexors symbolize the chief contributors of this required muscle work. It is believed that in stroke patients, these lower limb muscles of the affected side lose their capabilities to generate the normal levels of muscular forces.9 Recent studies on quantitative gait analyses of hemiparetic patients using computer dynography (CDG) have indicated that temporal and distance parameters are clinically useful indicators for assessment of their gait performance and monitoring of functional recovery.10To enable stroke patients to achieve these goals, therapists designing a gait-retraining program should first identify the primary underlying impairments that account for the reduced gait velocity and asymmetry of these patients. However, there is hardly any study about quantitative analysis of gait parameters and the impairments that are the most important factors in determining gait velocity and asymmetry of stroke patients.11Hence the present study was aimed to find out the asymmetriesin gait parameters in a stroke patient.
Case Description
The patient (Mr.V.G.) was a 72 year old bank manager. He was referred for stroke rehabilitation by Neurologist. The case was attended by Physiotherapist and enrolled on daily treatment basis.
Patient History
Mr. V.G. complained of difficulty in moving his left upper and lower extremity since one and half year. He was diagnosed as right side cerebrovascular accident (CVA) with left side weakness. He was known cigarette smoker for past thirty years.He had been suffering from hypertension since last thirteen years and since then he was on antihypertensive drugs.
Physical Examination
Physical examination was performed by the investigators and it was found this patient had typical hemiplegic posture,STREAM (Stroke Rehabilitation Assessment of Movement)score was 32/40 for voluntary control and 21/30 for basic mobility,Berg balance score was 36/56, dynamic gait index 20/24, intact sensation and his blood pressure was 140/90. Magnetic Resonance Imaging (MRI) brain reports revealed large right Middle Cerebral Artery (MCA) territory infarct and generalised cerebral atrophy.
Computerised Dynography Evaluation
The computerised dynographic evaluation of Mr. V. G. was performed with CDG® system manufactured by Infotronic, Netherlands, http://www.infotronic.nl. This system consists of sensor shoes, connecting cables, internal memory unit and computer with ultra tech software. The CDG system (figure 1)provides quantitative data about histogram, cyclogram, gait line,force gait line, step times and force graphics.Prior to the dynographic evaluation, patient was informed about the procedure and an informed written consent was obtained. Then internal memory unit was connected to the computer and settings of force value under each sensor was sampled at a rate of 50Hz, for two minutes walking period and stored in the software. Patient wore loose short trouser to avoid any discomfort. Then sensor shoes(Figure 2) were worn by the patient, which were connected using connecting cable to internal memory unit attached to the back of patient with waist belt (Figure 3). A trial test was performed to make sure that the patient was at an ease with instrument and the procedure. Then 20 minute rest interval was given as a washout period prior to the final assessment. After this, actual gait evaluation was done in which he was asked to walk over a walkway of 10 meters to and fro at comfortable speed for two minutes. After this,sensor shoes and internal memory unit was removed and data was transferred from internal memory unit to the computer for data analysis. Patient completed the distance of 30 feet in 2 minutes. Four base support stick was use by the patient during walking.
Results
CDG revealed abnormal changes in cyclogram, histogram,gait line, force gait line, step time and force graphics gait pattern suggesting pathological gait asymmetry. Cyclogram (figure 4)represents the kinematics during total gait cycle. Cyclogram revealed a shift in centre of gravity and concentration of force lines on unaffected side suggesting maximum weight bearing on unaffected side during the whole gait cycle. Histogram (figure5) represents the amount of force borne by each of eight shoe sensors during the gait cycle. Histogram of this patient showed an excessive increase in weight bearing on unaffected foot from heel to toe with heel bearing 66% weight. The interesting fact noted here was increased weight bearing on medial border of unaffected foot suggesting flat foot. Gait line (figure 6) and force gait line (figure 7) is concentration of forces starting from heel to toe. In this patient, it was altered on affected side and started from mid foot instead of heel and continued to forefoot suggestive of abnormal weight bearing pattern on affected side. Step times(figure 8) represent all temporal parameters in terms gait cycle, frequency, single support time, double support time, single swing, stance time and step time. In this case, gait cycle was 3.96seconds, frequency/minute was 30, left single support time was0.370 seconds, right single support time was 0.658 seconds, left double support time was 1.606 and right double support time was1.329, left single swing time was 0.658seconds, right single swing time was 0.370 seconds, left stance time was 3.305 seconds, right stance time was 3.596, left step time was 1.976 seconds, right step time was 1.987 seconds and symmetry ratio was 0.99. Force graphics (figure 9) represents the sum of forces on sensors during gait cycle. In the present patient, it showed a 750 N on left side and850 N on right side. In summary, there was 61% reduction in single support time, eight times increased in double support time on affected side and decreased frequency by 23.8%.
Discussion
Results of this study showed abnormal changes in cyclogram, histogram, gait line, force gait line, step time and force graphics gait pattern suggesting pathological gait asymmetry. This could be due to various pathological factors,such as abnormalities in motor control, motor impairment,presences of compensatory strategies and spasticity. The results are partly in accordance to the study performed by Wong etal12 who investigated the feasibility of using a foot contact pattern to predict neurologic recovery and the effect of ambulation training in hemiplegic stroke patients with conventional gait analysis system (6 cameras) and the portable ComputerDynoGraphy (CDG) system and found negative correlation between the Brunnstrom stages and the foot contact patterns.Clinical implications of CDG for stroke patients may include detection of abnormality, treatment planning and prognosis. Obvious limitation of this study includes difficulty in generalising its outcome and hence future randomised controlled trials can be done to investigate further pathophysiology pertaining to the gait deviations in stroke patients.
Conclusion
CDG is one of the useful clinical tools for the assessment of gait asymmetries in terms of force and temporal parameters variations in stroke.
College of Physiotherapy, Pravara Institute of Medical Sciences (PIMS), Loni, Maharashtra State, India - 413736
Abstract
The purpose of this study was to assess the gait asymmetries in terms of temporal and force gait parametersusing Computer Dynography (CDG) system in a hemiparetic person. A 72 year male patient diagnosed as right sided cerebrovascular accident was referred to physiotherapy department with complaints of weakness in left upper & lower limbs and difficulty in walking in terms of impaired foot clearance since one and half year. His computerised gait dynography was done with Computer DynoGraphy (CDG)® system (Infotronic,Netherlands, http://www.infotronic.nl).It was found that there was asymmetry in his cyclogram,gait line, histogram, force gait line, force graphic, step times which included gait cycle, frequency, symmetry ratio, single support time, double support time, single swing, stance time and step time. Hence, it was concluded that CDG may be considered as one of the useful clinical tool for the assessment of gait asymmetries in hemiparetic patient so as to plan therapeutic interventions.
Key Words
Computer dynography, cyclogram, force graphics,histogram & hemiparesis.
Introduction
Stroke is considered to be a leading cause of disability throughout the world.1 The reported annual incidence of stroke in India is around 130 per one lakh population with an equal gender ratio. Further, it has been estimated that about 20 percent of patients with heart ailments are susceptible to stroke.2 After an initial period of high mortality, survival from stroke is generally good, with 50% of stroke patients alive for 7 years post stroke.3,4 Although, neurological impairments may resolve spontaneously or decrease following rehabilitation, persisting disabilities leading to partial or total dependence in activity of daily life (ADL) can still be present in 30 to 60 % of stroke survivors. More than 85%of stroke survivors can eventually walk with or without assistance.1, 5 Common features of walking after stroke include decreased gait velocity and asymmetrical gait pattern.6-7 It is suggested that in stroke patients, almost 40% of the required muscle work is performed by the muscles of the affected side during walking.8 Hip flexors, knee extensors and ankle plantarflexors symbolize the chief contributors of this required muscle work. It is believed that in stroke patients, these lower limb muscles of the affected side lose their capabilities to generate the normal levels of muscular forces.9 Recent studies on quantitative gait analyses of hemiparetic patients using computer dynography (CDG) have indicated that temporal and distance parameters are clinically useful indicators for assessment of their gait performance and monitoring of functional recovery.10To enable stroke patients to achieve these goals, therapists designing a gait-retraining program should first identify the primary underlying impairments that account for the reduced gait velocity and asymmetry of these patients. However, there is hardly any study about quantitative analysis of gait parameters and the impairments that are the most important factors in determining gait velocity and asymmetry of stroke patients.11Hence the present study was aimed to find out the asymmetriesin gait parameters in a stroke patient.
Case Description
The patient (Mr.V.G.) was a 72 year old bank manager. He was referred for stroke rehabilitation by Neurologist. The case was attended by Physiotherapist and enrolled on daily treatment basis.
Patient History
Mr. V.G. complained of difficulty in moving his left upper and lower extremity since one and half year. He was diagnosed as right side cerebrovascular accident (CVA) with left side weakness. He was known cigarette smoker for past thirty years.He had been suffering from hypertension since last thirteen years and since then he was on antihypertensive drugs.
Physical Examination
Physical examination was performed by the investigators and it was found this patient had typical hemiplegic posture,STREAM (Stroke Rehabilitation Assessment of Movement)score was 32/40 for voluntary control and 21/30 for basic mobility,Berg balance score was 36/56, dynamic gait index 20/24, intact sensation and his blood pressure was 140/90. Magnetic Resonance Imaging (MRI) brain reports revealed large right Middle Cerebral Artery (MCA) territory infarct and generalised cerebral atrophy.
Computerised Dynography Evaluation
The computerised dynographic evaluation of Mr. V. G. was performed with CDG® system manufactured by Infotronic, Netherlands, http://www.infotronic.nl. This system consists of sensor shoes, connecting cables, internal memory unit and computer with ultra tech software. The CDG system (figure 1)provides quantitative data about histogram, cyclogram, gait line,force gait line, step times and force graphics.Prior to the dynographic evaluation, patient was informed about the procedure and an informed written consent was obtained. Then internal memory unit was connected to the computer and settings of force value under each sensor was sampled at a rate of 50Hz, for two minutes walking period and stored in the software. Patient wore loose short trouser to avoid any discomfort. Then sensor shoes(Figure 2) were worn by the patient, which were connected using connecting cable to internal memory unit attached to the back of patient with waist belt (Figure 3). A trial test was performed to make sure that the patient was at an ease with instrument and the procedure. Then 20 minute rest interval was given as a washout period prior to the final assessment. After this, actual gait evaluation was done in which he was asked to walk over a walkway of 10 meters to and fro at comfortable speed for two minutes. After this,sensor shoes and internal memory unit was removed and data was transferred from internal memory unit to the computer for data analysis. Patient completed the distance of 30 feet in 2 minutes. Four base support stick was use by the patient during walking.
Results
CDG revealed abnormal changes in cyclogram, histogram,gait line, force gait line, step time and force graphics gait pattern suggesting pathological gait asymmetry. Cyclogram (figure 4)represents the kinematics during total gait cycle. Cyclogram revealed a shift in centre of gravity and concentration of force lines on unaffected side suggesting maximum weight bearing on unaffected side during the whole gait cycle. Histogram (figure5) represents the amount of force borne by each of eight shoe sensors during the gait cycle. Histogram of this patient showed an excessive increase in weight bearing on unaffected foot from heel to toe with heel bearing 66% weight. The interesting fact noted here was increased weight bearing on medial border of unaffected foot suggesting flat foot. Gait line (figure 6) and force gait line (figure 7) is concentration of forces starting from heel to toe. In this patient, it was altered on affected side and started from mid foot instead of heel and continued to forefoot suggestive of abnormal weight bearing pattern on affected side. Step times(figure 8) represent all temporal parameters in terms gait cycle, frequency, single support time, double support time, single swing, stance time and step time. In this case, gait cycle was 3.96seconds, frequency/minute was 30, left single support time was0.370 seconds, right single support time was 0.658 seconds, left double support time was 1.606 and right double support time was1.329, left single swing time was 0.658seconds, right single swing time was 0.370 seconds, left stance time was 3.305 seconds, right stance time was 3.596, left step time was 1.976 seconds, right step time was 1.987 seconds and symmetry ratio was 0.99. Force graphics (figure 9) represents the sum of forces on sensors during gait cycle. In the present patient, it showed a 750 N on left side and850 N on right side. In summary, there was 61% reduction in single support time, eight times increased in double support time on affected side and decreased frequency by 23.8%.
Discussion
Results of this study showed abnormal changes in cyclogram, histogram, gait line, force gait line, step time and force graphics gait pattern suggesting pathological gait asymmetry. This could be due to various pathological factors,such as abnormalities in motor control, motor impairment,presences of compensatory strategies and spasticity. The results are partly in accordance to the study performed by Wong etal12 who investigated the feasibility of using a foot contact pattern to predict neurologic recovery and the effect of ambulation training in hemiplegic stroke patients with conventional gait analysis system (6 cameras) and the portable ComputerDynoGraphy (CDG) system and found negative correlation between the Brunnstrom stages and the foot contact patterns.Clinical implications of CDG for stroke patients may include detection of abnormality, treatment planning and prognosis. Obvious limitation of this study includes difficulty in generalising its outcome and hence future randomised controlled trials can be done to investigate further pathophysiology pertaining to the gait deviations in stroke patients.
Conclusion
CDG is one of the useful clinical tools for the assessment of gait asymmetries in terms of force and temporal parameters variations in stroke.
Figures and graphs at link.
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