Usability and Reliability of the Edinburgh Visual Gait Score in Children with Spastic Cerebral Palsy Using Smartphone Slow-Motion Video Technology and a Motion Analysis Application: A Pilot Study

Clinical study on the safety and feasibility of AiWalker-K for lower limbs exercise rehabilitation in children with cerebral palsy

BACKGROUND

Robotic-assisted gait training (RAGT) devices are effective for children with cerebral palsy (CP). Many RAGT devices have been created and put into clinical rehabilitation treatment. Therefore, we aimed to investigate the safety and feasibility of a new RAGT for children with CP.

METHODS

This study is a cross-over design with 23 subjects randomly divided into two groups. The occurrence of adverse events and changes in heart rate and blood pressure were recorded during each AiWalker-K training. Additionally, Gross Motor Function Measure-88 (GMFM-88), Pediatric Balance Scale (PBS), 6 Minutes Walking Test (6MWT), Physiological Cost Index, and Edinburgh Visual Gait Score (EVGS) were used to assess treatment, period, carry-over, and follow-up effects in this study.

RESULTS

Adverse events included joint pain, skin pain, and injury. Heart rate and blood pressure were higher with the AiWalker-K compared to the rest (P < 0.05), but remained within safe ranges. After combined treatment with AiWalker-K and routine rehabilitation treatment, significant improvements in 6MWT, GMFM-88 D and E, PBS, and EVGS were observed compared to routine rehabilitation treatment alone (P < 0.05).

CONCLUSIONS

Under the guidance of experienced medical personnel, AiWalker-K can be used for rehabilitation in children with CP.

Slow-motion smartphone video improves interobserver reliability of gait assessment in ambulatory cerebral palsy

Purpose

Structured visual gait assessment is essential for the evaluation of pediatric patients with neuromuscular conditions. The purpose of this study was to evaluate the benefit of slow-motion video recorded on a standard smartphone to augment visual gait assessment.

Methods

Coronal and sagittal plane videos of the gait of five pediatric subjects were recorded on a smartphone, including four subjects with ambulatory cerebral palsy and one subject without gait pathology. Twenty-one video scorers were recruited and randomized to evaluate slow-motion or normal-speed videos utilizing the Edinburgh Visual Gait Score. The slow-motion group (N = 11) evaluated the videos at one-eighth speed, and the normal-speed group (N = 10) evaluated the same videos at normal speed. Interrater reliabilities were determined by calculating intraclass correlation coefficients for each group as a whole, for each Edinburgh Visual Gait Score item, and after stratification by evaluator experience level.

Results

The slow-motion group exhibited an intraclass correlation coefficient of 0.65 (95% confidence interval: 0.58-0.73), whereas the normal-speed group exhibited an intraclass correlation coefficient of 0.57 (95% confidence interval: 0.49-0.65). For less-experienced scorers, intraclass correlation coefficients of 0.62 (95% confidence interval: 0.53-0.71) and 0.50 (95% confidence interval: 0.40-0.59) were calculated for slow motion and normal speed, respectively. For more-experienced scorers, intraclass correlation coefficients of 0.69 (95% confidence interval: 0.61-0.76) and 0.67 (95% confidence interval: 0.58-0.75) were calculated for slow motion and normal speed, respectively.

Conclusions

Visual gait assessment is enhanced by the use of slow-motion smartphone video, a tool widely available throughout the world with no marginal cost.

Level of evidence

level I, randomized study.

Automated Implementation of the Edinburgh Visual Gait Score (EVGS) Using OpenPose and Handheld Smartphone Video

Recent advancements in computing and artificial intelligence (AI) make it possible to quantitatively evaluate human movement using digital video, thereby opening the possibility of more accessible gait analysis. The Edinburgh Visual Gait Score (EVGS) is an effective tool for observational gait analysis, but human scoring of videos can take over 20 min and requires experienced observers. This research developed an algorithmic implementation of the EVGS from handheld smartphone video to enable automatic scoring. Participant walking was video recorded at 60 Hz using a smartphone, and body keypoints were identified using the OpenPose BODY25 pose estimation model. An algorithm was developed to identify foot events and strides, and EVGS parameters were determined at relevant gait events. Stride detection was accurate within two to five frames. The level of agreement between the algorithmic and human reviewer EVGS results was strong for 14 of 17 parameters, and the algorithmic EVGS results were highly correlated (r > 0.80, "r" represents the Pearson correlation coefficient) to the ground truth values for 8 of the 17 parameters. This approach could make gait analysis more accessible and cost-effective, particularly in areas without gait assessment expertise. These findings pave the way for future studies to explore the use of smartphone video and AI algorithms in remote gait analysis.

Effect of hip CPM on gross motor function and development of the hip joint: a single-center randomized controlled study on spastic cerebral palsy children with hip dysplasia

Objective

To investigate the effectiveness of hip continuous passive motion (hCPM) on hip development at skeletal maturity and gross motor function for spastic cerebral palsy children with hip dysplasia.

Methods

Prospective case-control research of hCPM with goal-directed training versus merely goal-directed training. On the basis of goal-directed training, the hCPM group used the hip joint CPM instrument (the external fixator was connected to the power device to make the hip joint carry out continuous passive movement) for 40-60 min, twice a day, and five times a week, and received continuous training for 8 weeks simultaneously. The control group received only goal-directed training for 8 weeks. Functional outcomes pertaining to the affected hip joints were assessed via gross motor function measure (GMFM), migration percentage (MP), acetabular index (AI), and Harris hip functional score (HHS) at the time of enrollment and the end of the intervention.

Results

The case-control research included 65 participants (mean age = 46.20 months, SD = 17.09 months; Gross Motor Function Grading System level: III = 41, IV = 24) who were randomly selected to either the hCPM (n = 45) or the control group (n = 20). No differences were found in baseline (acquisition phase) GMFM, MP, AI, or HHS (t = -1.720, P = 0.090; t* = 1.836, P* = 0.071; t# = -1.517, P# = 0.139; t* = -1.310, P* = 0.195; t# = -1.084, P# = 0.097; t = -1.041, P = 0.301). At the 8-week follow-up, GMFM, MP, AI, and HHS significantly improved over baseline in the hCPM group (hCPM group: t = 18.59, 20.172*, 40.291#, 16.820*, 32.900#, 28.081; P < 0.001). Between-group differences at 8-week follow-up times points favored the hCPM group for GMFM (t = -2.637, P = 0.011), MP (t* = 2.615, P* = 0.014; t# = 3.000, P# = 0.006), AI (t* = 2.055, P* = 0.044; t# = 2.223, P# = 0.030), HHS (t = -4.685, P < 0.001) (*: left side; #: right side).

Conclusion

Spastic cerebral palsy children with hip dysplasia achieved meaningful functional improvement after 8 weeks of goal-directed training with hCPM therapy.

Inter- and intra-rater reliability of new application software for computerised paediatric version of Wisconsin Gait Scale

The paediatric version of Wisconsin Gait Scale (WGS) is a reliable tool for gait assessment in children with spastic hemiplegic cerebral palsy (CP). We decided to develop a solution which will make it possible to objectify the descriptive paediatric version of the WGS, and which, consequently, will allow researchers/clinicians to more easily perform accurate assessment of gait patterns in patients. The aim of the study was to assess inter- and intra-rater reliability of new application software for computerised paediatric version of the WGS in children with hemiplegic CP. The study involved 31 children with hemiplegic CP. The app was designed using a model based on thematic categories of the paediatric WGS, and utilising auxiliary lines between specific points on the patient's body, and taking into account angular values, duration and length of the specific gait phases, in order to enable acquisition of quantitative data corresponding to the components of the WGS. The gait of the study participants was recorded, in series of videos. These provided material for three independent raters who reviewed the recordings twice and assessed the participants' gait using the app. After the evaluation was completed, the data were retrieved from the software. The new application software for the computerised paediatric WGS presents very good inter- and intra-rater reliability. Intra-class correlation coefficient (ICC) was very high in measurement 1 (ICC > 0.9) and 2 (ICC > 0.8), which reflects a very high degree of agreement between the three examiners; there was also high agreement for the specific examiners, between the two measurements (ICC > 0.9). The observational gait scale, objectified through the new software, and enabling computer-aided use of the paediatric WGS, presents practical advantages for examiners since it facilitates decisions taken in the process of WGS-based assessment in children with spastic hemiplegic CP.