Instrumented Gait Classification Using Meaningful Features in Patients with Impaired Coordination
Early onset ataxia (EOA) and developmental coordination disorder (DCD) both affect cerebellar functioning in children, making the clinical distinction challenging. We here aim to derive meaningful features from quantitative SARA-gait data (i.e., the gait test of the scale for the assessment and rati...
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| Format: | Article |
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MDPI AG
2023-10-01
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| Series: | Sensors |
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| Online Access: | https://www.mdpi.com/1424-8220/23/20/8410 |
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| author | Zeus T. Dominguez-Vega Mariano Bernaldo de Quiros Jan Willem J. Elting Deborah A. Sival Natasha M. Maurits |
| author_facet | Zeus T. Dominguez-Vega Mariano Bernaldo de Quiros Jan Willem J. Elting Deborah A. Sival Natasha M. Maurits |
| author_sort | Zeus T. Dominguez-Vega |
| collection | DOAJ |
| description | Early onset ataxia (EOA) and developmental coordination disorder (DCD) both affect cerebellar functioning in children, making the clinical distinction challenging. We here aim to derive meaningful features from quantitative SARA-gait data (i.e., the gait test of the scale for the assessment and rating of ataxia (SARA)) to classify EOA and DCD patients and typically developing (CTRL) children with better explainability than previous classification approaches. We collected data from 18 EOA, 14 DCD and 29 CTRL children, while executing both SARA gait tests. Inertial measurement units were used to acquire movement data, and a gait model was employed to derive meaningful features. We used a random forest classifier on 36 extracted features, leave-one-out-cross-validation and a synthetic oversampling technique to distinguish between the three groups. Classification accuracy, probabilities of classification and feature relevance were obtained. The mean classification accuracy was 62.9% for EOA, 85.5% for DCD and 94.5% for CTRL participants. Overall, the random forest algorithm correctly classified 82.0% of the participants, which was slightly better than clinical assessment (73.0%). The classification resulted in a mean precision of 0.78, mean recall of 0.70 and mean F1 score of 0.74. The most relevant features were related to the range of the hip flexion–extension angle for gait, and to movement variability for tandem gait. Our results suggest that classification, employing features representing different aspects of movement during gait and tandem gait, may provide an insightful tool for the differential diagnoses of EOA, DCD and typically developing children. |
| first_indexed | 2024-03-10T20:54:18Z |
| format | Article |
| id | doaj.art-02f79fe95ce04e10b9d7ad026630d8b7 |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-03-10T20:54:18Z |
| publishDate | 2023-10-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-02f79fe95ce04e10b9d7ad026630d8b72023-11-19T18:02:28ZengMDPI AGSensors1424-82202023-10-012320841010.3390/s23208410Instrumented Gait Classification Using Meaningful Features in Patients with Impaired CoordinationZeus T. Dominguez-Vega0Mariano Bernaldo de Quiros1Jan Willem J. Elting2Deborah A. Sival3Natasha M. Maurits4Department of Neurology, University Medical Center Groningen, University of Groningen, 9713 GZ Groningen, The NetherlandsDepartment of Neurology, University Medical Center Groningen, University of Groningen, 9713 GZ Groningen, The NetherlandsDepartment of Neurology, University Medical Center Groningen, University of Groningen, 9713 GZ Groningen, The NetherlandsDepartment of Paediatrics, Beatrix Children’s Hospital, University Medical Center Groningen, University of Groningen, 9713 GZ Groningen, The NetherlandsDepartment of Neurology, University Medical Center Groningen, University of Groningen, 9713 GZ Groningen, The NetherlandsEarly onset ataxia (EOA) and developmental coordination disorder (DCD) both affect cerebellar functioning in children, making the clinical distinction challenging. We here aim to derive meaningful features from quantitative SARA-gait data (i.e., the gait test of the scale for the assessment and rating of ataxia (SARA)) to classify EOA and DCD patients and typically developing (CTRL) children with better explainability than previous classification approaches. We collected data from 18 EOA, 14 DCD and 29 CTRL children, while executing both SARA gait tests. Inertial measurement units were used to acquire movement data, and a gait model was employed to derive meaningful features. We used a random forest classifier on 36 extracted features, leave-one-out-cross-validation and a synthetic oversampling technique to distinguish between the three groups. Classification accuracy, probabilities of classification and feature relevance were obtained. The mean classification accuracy was 62.9% for EOA, 85.5% for DCD and 94.5% for CTRL participants. Overall, the random forest algorithm correctly classified 82.0% of the participants, which was slightly better than clinical assessment (73.0%). The classification resulted in a mean precision of 0.78, mean recall of 0.70 and mean F1 score of 0.74. The most relevant features were related to the range of the hip flexion–extension angle for gait, and to movement variability for tandem gait. Our results suggest that classification, employing features representing different aspects of movement during gait and tandem gait, may provide an insightful tool for the differential diagnoses of EOA, DCD and typically developing children.https://www.mdpi.com/1424-8220/23/20/8410early onset ataxiadevelopmental coordination disordergait assessmentinertial measurement unitsrandom forest classifier |
| spellingShingle | Zeus T. Dominguez-Vega Mariano Bernaldo de Quiros Jan Willem J. Elting Deborah A. Sival Natasha M. Maurits Instrumented Gait Classification Using Meaningful Features in Patients with Impaired Coordination Sensors early onset ataxia developmental coordination disorder gait assessment inertial measurement units random forest classifier |
| title | Instrumented Gait Classification Using Meaningful Features in Patients with Impaired Coordination |
| title_full | Instrumented Gait Classification Using Meaningful Features in Patients with Impaired Coordination |
| title_fullStr | Instrumented Gait Classification Using Meaningful Features in Patients with Impaired Coordination |
| title_full_unstemmed | Instrumented Gait Classification Using Meaningful Features in Patients with Impaired Coordination |
| title_short | Instrumented Gait Classification Using Meaningful Features in Patients with Impaired Coordination |
| title_sort | instrumented gait classification using meaningful features in patients with impaired coordination |
| topic | early onset ataxia developmental coordination disorder gait assessment inertial measurement units random forest classifier |
| url | https://www.mdpi.com/1424-8220/23/20/8410 |
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