Automatic Assessment of Arm Motor Function and Postural Stability in Virtual Scenarios: Towards a Virtual Version of the Fugl-Meyer Test

Oña, Edwin Daniel; Jardón, Alberto; Balaguer, Carlos

doi:10.1109/segah49190.2020.9201758

Cited by 3 publications

(3 citation statements)

References 22 publications

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“…This approach requires a large amount of data annotation and the results validated on a small data set are not convincing. Oña et al [17] proposed a virtual version of the FMA scale test using the serious game to assess patients' upper limb abilities and balance abilities simultaneously. Although the above work has made some attempts to assess patients' motor impairment abilities using serious games, there are still major problems with the game design.…”

Section: B Automatic Assessment Methods For Motor Ability Based On Se...mentioning

confidence: 99%

“…Existing serious game-based upper limb assessment methods for stroke patients typically collect information about the patient's hand in real-time during game interaction and combine machine learning or neural network models to assess the patient [16], [17], [18]. Although several of these works have achieved good results in assessing patients' upper limb motor abilities based on serious games, there are still three problems.…”

Section: Introductionmentioning

confidence: 99%

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A Serious Game System for Upper Limb Motor Function Assessment of Hemiparetic Stroke Patients

Jiang

Liu

et al. 2023

IEEE Trans. Neural Syst. Rehabil. Eng.

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Stroke often results in hemiparesis, impairing the patient's motor abilities and leading to upper extremity motor deficits that require long-term training and assessment. However, existing methods for assessing patients' motor function rely on clinical scales that require experienced physicians to guide patients through target tasks during the assessment process. This process is not only time-consuming and labor-intensive, but the complex assessment process is also uncomfortable for patients and has significant limitations. For this reason, we propose a serious game that automatically assesses the degree of upper limb motor impairment in stroke patients. Specifically, we divide this serious game into a preparation stage and a competition stage. In each stage, we construct motor features based on clinical a priori knowledge to reflect the ability indicators of the patient's upper limbs. These features all correlated significantly with the Fugl-Meyer Assessment for Upper Extremity (FMA-UE), which assesses motor impairment in stroke patients. In addition, we design membership functions and fuzzy rules for motor features in combination with the opinions of rehabilitation therapists to construct a hierarchical fuzzy inference system to assess the motor function of upper limbs in stroke patients. In this study, we recruited a total of 24 patients with varying degrees of stroke and 8 healthy controls to participate in the Serious Game System test. The results show that our Serious Game System was able to effectively differentiate between controls, severe, moderate, and mild hemiparesis with an average accuracy of 93.5%.

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Section: B Automatic Assessment Methods For Motor Ability Based On Se...mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

A Serious Game System for Upper Limb Motor Function Assessment of Hemiparetic Stroke Patients

Jiang

Liu

et al. 2023

IEEE Trans. Neural Syst. Rehabil. Eng.

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“…While Nadinne Roman and colleagues translated and validated the Upper Extremity Functional Motor assessment scale (UEFMA) resulting a Romanian version of the UEFMA that showed excellent validity and reliability for post-stroke examination 13 . Edwin Daniel Ona proposed FMA to be a high-resolution, autonomous, and objective tool for motor assessment in neurorehabilitation 14 . The use of FMAUE would enable for comparisons of stroke recovery across regions and nations, thereby improving the quality of treatment and rehabilitation for stroke patients throughout the world 15 .…”

Section: Introductionmentioning

confidence: 99%

Normative Data of Fugl Meyer Assessment on Upper Extremity in Post Stroke Population

Yasmin

Tahir

Jabeen

et al. 2023

SJPTR

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Background: Stroke is clinically diagnosed as an acute, localized neurological impairment that is caused by vascular damage (infarction, hemorrhage) to the central nervous system. This main leading cause of demise and dysfunction worldwide resulting in frequent deficit, hemiplegia, which briefly affects upper limb. This multicentered study is the first to provide updated normative reference values for FMA-UE in post stroke adults in wide range of age in Pakistan’s population. Objective: To determine Pakistani normative values of Fugl-Meyer Assessment on upper extremity in post Stroke Population. Methods: Descriptive cross-sectional study on 1260 post-stroke patients was conducted in various public and private physiotherapy centers of country using Fugl-Meyer Assessment (Upper-Extremity) FMA-UE scale after ethical approval. Hemiplegic survivors of both genders aged 45-75 years were taken using convenience sampling technique, informed consent was taken. Statistics was done using SPSS version25. Results: Patients included were 88.3% ischemic and 11.7% hemorrhagic. 44.1% were in acute phase (less than 2 weeks) while 55.9% were in sub-acute (2 weeks to 6 months) phase. Mean score of FMA-UE was 88.63±30.09. The cutoff score/mean value for motor impairment and sensation was recorded as 41.49 ±19.7 and 8.6±3.9 while passive joint motion and pain were calculated 18.93±5.47 and 19.57±5.1 respectively. Conclusion: The scoring, in acute and subacute phases, accentuate the need to follow Pakistani specific modified norms in Asian inhabitants instead of reference values applicable on western population. Keywords: Fugl-Meyer scale, Hemiplegia, Motor control, Post Stroke, Upper extremity.

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Detection of Postural Control in Young and Elderly Adults Using Deep and Machine Learning Methods with Joint–Node Plots

Lee

Chen

Wang

et al. 2021

Sensors

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Postural control decreases with aging. Thus, an efficient and accurate method of detecting postural control is needed. We enrolled 35 elderly adults (aged 82.06 ± 8.74 years) and 20 healthy young adults (aged 21.60 ± 0.60 years) who performed standing tasks for 40 s, performed six times. The coordinates of 15 joint nodes were captured using a Kinect device (30 Hz). We plotted joint positions into a single 2D figure (named a joint–node plot, JNP) once per second for up to 40 s. A total of 15 methods combining deep and machine learning for postural control classification were investigated. The accuracy, sensitivity, specificity, positive predicted value (PPV), negative predicted value (NPV), and kappa values of the selected methods were assessed. The highest PPV, NPV, accuracy, sensitivity, specificity, and kappa values were higher than 0.9 in validation testing. The presented method using JNPs demonstrated strong performance in detecting the postural control ability of young and elderly adults.

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Automatic Assessment of Arm Motor Function and Postural Stability in Virtual Scenarios: Towards a Virtual Version of the Fugl-Meyer Test

Cited by 3 publications

References 22 publications

A Serious Game System for Upper Limb Motor Function Assessment of Hemiparetic Stroke Patients

A Serious Game System for Upper Limb Motor Function Assessment of Hemiparetic Stroke Patients

Normative Data of Fugl Meyer Assessment on Upper Extremity in Post Stroke Population

Detection of Postural Control in Young and Elderly Adults Using Deep and Machine Learning Methods with Joint–Node Plots

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