scholarly journals A-GAS: a Probabilistic Approach for Generating Automated Gait Assessment Score for Cerebral Palsy Children

Author(s):  
Rishabh Bajpai ◽  
Deepak Joshi

<pre><p>Gait disorders in children with cerebral palsy (CP) affect their mental, physical, economic, and social lives. Gait assessment is one of the essential steps of gait management. It has been widely used for clinical decision making and evaluation of different treatment outcomes. However, most of the present methods of gait assessment are subjective, less sensitive to small pathological changes, time-taking and need a great effort of an expert. This work proposes an automated, comprehensive gait assessment score (A-GAS) for gait disorders in CP. Kinematic data of 356 CP and 41 typically developing subjects is used to validate the performance of A-GAS. For the computation of A-GAS, instance abnormality index (AII) and abnormality index (AI) are calculated. AII quantifies gait abnormality of a gait cycle instance, while AI quantifies gait abnormality of a joint angle profile during walking. AII is calculated for all gait cycle instances by performing probabilistic and statistical analyses. Abnormality index (AI) is a weighted sum of AII, computed for each joint angle profile. A-GAS is a weighted sum of AI, calculated for a lower limb. Moreover, a graphical representation of the gait assessment report, including AII, AI, and A-GAS is generated for providing a better depiction of the assessment score. Furthermore, the work compares A-GAS with a present rating-based gait assessment scores to understand fundamental differences. Finally, A-GAS's performance is verified for a high-cost multi-camera set-up using nine joint angle profiles and a low-cost single camera set-up using three joint angle profiles. Results show no significant differences in performance of A-GAS for both the set-ups. Therefore, A-GAS for both the set-ups can be used interchangeably. </p> </pre>

2021 ◽  
Author(s):  
Rishabh Bajpai ◽  
Deepak Joshi

Gait disorders in children with cerebral palsy (CP) affect their mental, physical, economic, and social lives. Gait assessment is one of the essential steps of gait management. It has been widely used for clinical decision making and evaluation of different treatment outcomes. However, most of the present methods of gait assessment are subjective, less sensitive to small pathological changes, time-taking and need a great effort of an expert. This study proposes an automated, comprehensive gait assessment score (A-GAS) for gait disorders in CP. Kinematic data of 356 CP and 41 typically developing subjects is used to validate the performance of A-GAS. For the computation of A-GAS, instance abnormality index (AII) and abnormality index (AI) are computed. AII quantifies gait abnormality of a gait cycle instance, while AI quantifies gait abnormality of a joint angle profile. AII is calculated for all gait cycle instances by performing probabilistically and statistical tests. Abnormality index (AI) is a weighted sum of AII, computed for each joint angle profile. A-GAS is a weighted sum of AI, calculated for a lower limb. Moreover, a graphical representation of the gait assessment report, including AII, AI, and A-GAS is generated to understand the results better. Furthermore, the study compares A-GAS with a present rating-based gait assessment scores to understand fundamental differences between them. Finally, AGAS’s performance is verified for a high-cost multicamera set-up using nine joint angle profiles and a low-cost single camera set-up using three joint angle profiles. Results show no significant differences in performance of A-GAS for both the set-ups. Therefore, A-GAS for both the set-ups can be used interchangeably.


2021 ◽  
Author(s):  
Rishabh Bajpai ◽  
Deepak Joshi

Gait disorders in children with cerebral palsy (CP) affect their mental, physical, economic, and social lives. Gait assessment is one of the essential steps of gait management. It has been widely used for clinical decision making and evaluation of different treatment outcomes. However, most of the present methods of gait assessment are subjective, less sensitive to small pathological changes, time-taking and need a great effort of an expert. This study proposes an automated, comprehensive gait assessment score (A-GAS) for gait disorders in CP. Kinematic data of 356 CP and 41 typically developing subjects is used to validate the performance of A-GAS. For the computation of A-GAS, instance abnormality index (AII) and abnormality index (AI) are computed. AII quantifies gait abnormality of a gait cycle instance, while AI quantifies gait abnormality of a joint angle profile. AII is calculated for all gait cycle instances by performing probabilistically and statistical tests. Abnormality index (AI) is a weighted sum of AII, computed for each joint angle profile. A-GAS is a weighted sum of AI, calculated for a lower limb. Moreover, a graphical representation of the gait assessment report, including AII, AI, and A-GAS is generated to understand the results better. Furthermore, the study compares A-GAS with a present rating-based gait assessment scores to understand fundamental differences between them. Finally, AGAS’s performance is verified for a high-cost multicamera set-up using nine joint angle profiles and a low-cost single camera set-up using three joint angle profiles. Results show no significant differences in performance of A-GAS for both the set-ups. Therefore, A-GAS for both the set-ups can be used interchangeably.


2020 ◽  
Vol 11 (04) ◽  
pp. 640-642
Author(s):  
Halil Onder

AbstractGait disorders are common in the elderly as there are various causes of neurological and non-neurological conditions. On the other hand, most of the gait parameters do change with advancing age which is identified as age-related physiological changes in gait. At this point, the discrimination between age-related physiological changes and gait disorders may be strictly challenging. After identifying gait as an abnormal pattern, classification of it and making the responsible pathophysiology also require high-level expertise in this regard. Herein, we present a rare patient with corticobasal degeneration (CBD) who had admitted initially due to complaints of gait problems. Over a long time, the patient had received the misdiagnosis of gait abnormality due to musculoskeletal problems by multiple physicians. However, the detailed neurological exam showed a higher level gait disorder (HLGD). Further investigations at this point yielded the diagnosis of CBD.


2021 ◽  
pp. 263208432110100
Author(s):  
Satyendra Nath Chakrabartty

Background Scales for evaluating insomnia differ in number of items, response format, and result in different scores distributions and score ranges and may not facilitate meaningful comparisons. Objectives Transform ordinal item-scores of three scales of insomnia to continuous, equidistant, monotonic, normally distributed scores, avoiding limitations of summative scoring of Likert scales. Methods Equidistant item-scores by weighted sum using data-driven weights to different levels of different items, considering cell frequencies of Item-Levels matrix, followed by normalization and conversion to [1, 10]. Equivalent test-scores (as sum of transformed item- scores) for a pair of scales were found by Normal Probability curves. Empirical illustration given. Results Transformed test-scores are continuous, monotonic and followed Normal distribution with no outliers and tied scores. Such test-scores facilitate ranking, better classification and meaningful comparison of scales of different lengths and formats and finding equivalent score combinations of two scales. For a given value of transformed test-score of a scale, easy alternate method avoiding integration proposed to find equivalent scores of another scales. Equivalent scores of scales help to relate various cut-off scores of different scales and uniformity in interpretations. Integration of various scales of insomnia is achieved by finding one-to-one correspondence among the equivalent score of various scales with correlation over 0.99 Conclusion Resultant test-scores facilitated undertaking analysis in parametric set up. Considering the theoretical advantages including meaningfulness of operations, better comparison, use of such method of transforming scores of Likert items/test is recommended test and items, Future studies were suggested.


2021 ◽  
Vol 90 ◽  
pp. 1-8
Author(s):  
Rebecca A. States ◽  
Joseph J. Krzak ◽  
Yasser Salem ◽  
Ellen M. Godwin ◽  
Amy Winter Bodkin ◽  
...  

2012 ◽  
Vol 35 (2) ◽  
pp. 186-191 ◽  
Author(s):  
Kerstin L. Larsen ◽  
Grethe Maanum ◽  
Kathrine F. Frøslie ◽  
Reidun Jahnsen

2017 ◽  
Vol 2017 ◽  
pp. 1-8 ◽  
Author(s):  
Xin Chen ◽  
Xudong Zhang ◽  
Wenxiu Shi ◽  
Jun Wang ◽  
Yun Xiang ◽  
...  

Quantitative evaluation of the hemiparesis status for a poststroke patient is still challenging. This study aims to measure and investigate the dynamic muscle behavior in poststroke hemiparetic gait using ultrasonography. Twelve hemiparetic patients walked on a treadmill, and EMG, joint angle, and ultrasonography were simultaneously recorded for the gastrocnemius medialis muscle. Pennation angle was automatically extracted from ultrasonography using a tracking algorithm reported previously. The characteristics of EMG, joint angle, and pennation angle in gait cycle were calculated for both (affected and unaffected) sides of lower limbs. The results suggest that pennation angle could work as an important morphological index to continuous muscle contraction. The change pattern of pennation angle between the affected and unaffected sides is different from that of EMG. These findings indicate that morphological parameter extracted from ultrasonography can provide different information from that provided by EMG for hemiparetic gait.


2000 ◽  
Vol 20 (2) ◽  
pp. 217-220 ◽  
Author(s):  
Seref Aktas ◽  
Michael D. Aiona ◽  
Michael Orendurff

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