Assessments are completely worthless unless they point directly to the 100% recovery protocols. I see nothing here that suggests you go from the assessment to the chosen 100% recovery protocol. When the hell will the stroke medical world do ANYTHING TO GET STROKE SOLVED? I'd have you all fired! A lot of dead wood needs to removed in stroke and until that occurs stroke will never be solved!
I never had the box and block test, it would have been totally useless by the time spasticity occurred in my hand.
Ηand dexterities assessment in stroke patients based on augmented reality and machine learning through a box and block test
Scientific Reports volume 14, Article number: 10598 (2024)
Abstract
A popular and widely suggested measure for assessing unilateral hand motor skills in stroke patients is the box and block test (BBT). Our study aimed to create an augmented reality enhanced version of the BBT (AR-BBT) and evaluate its correlation to the original BBT for stroke patients. Following G-power analysis, clinical examination, and inclusion–exclusion criteria, 31 stroke patients were included in this study. AR-BBT was developed using the Open Source Computer Vision Library (OpenCV). The MediaPipe's hand tracking library uses a palm and a hand landmark machine learning model to detect and track hands. A computer and a depth camera were employed in the clinical evaluation of AR-BBT following the principles of traditional BBT. A strong correlation was achieved between the number of blocks moved in the BBT and the AR-BBT on the hemiplegic side (Pearson correlation = 0.918) and a positive statistically significant correlation (p = 0.000008). The conventional BBT is currently the preferred assessment method. However, our approach offers an advantage, as it suggests that an AR-BBT solution could remotely monitor the assessment of a home-based rehabilitation program and provide additional hand kinematic information for hand dexterities in AR environment conditions. Furthermore, it employs minimal hardware equipment.
Introduction
Nearly 80% of stroke patients suffer from upper extremity disabilities, such as unilateral paresis and sensory abnormalities1. Such disorders might cause reduced hand function, leading to exercise restriction and engagement behavioral inhibition2. Most of the patients recover gradually from such deficiencies, frequently attaining maximal recovery after 6–12 months of treatment3. It is recommended that patients are frequently evaluated at multiple time periods to review prognoses and design treatment strategies. Therefore, experts advocate regular monitoring and evaluation using validated and objective markers4.
A popular and widely accepted measure for assessing unilateral hand motor skills is the box and block test (BBT)5,6. Its original form consists of a box with two compartments separated in the middle by a barrier and 150 cubes of approximately 1 in3 each. The test uses the same hand to score the highest possible number of cubes from the compartment of the examined hemiparetic side to the opposite (horizontal adduction movement of the examined arm (Fig. 1). The number of accurately relocated blocks within 60 s determines the test's score. The BBT has demonstrated excellent inter- and intra-examiner reliability and represents a valid procedure for patients suffering from neurological disorders6,7,8,9,10,11.
As the stroke rate rises, neurorehabilitation and developing innovative, efficient treatment approaches utilizing virtual reality (VR) and augmented reality (AR) solutions are increasingly important. AR can facilitate the delivery of goal-oriented activities, sensorimotor and performance feedback, and enhanced intervention results12,13,14,15. Several studies have revealed that AR/VR might increase patient compliance by promoting their motivation16,17. Including entertaining parts in the treatment, such as those provided by serious games, can be valuable in this direction18. Moreover, when equipped with an autonomous headgear, VR allows patients to execute their treatment at home. Most AR/VR systems can monitor hand motions using infrared cameras or inertial measurement unit-integrated controllers. The use of fully immersive VR technology to perform functional evaluation and analyze upper extremity kinematics in post-stroke rehabilitation2 has not been investigated yet.
There is high scientific reasoning behind the development of AR tests. Using the automatic computing of quantitative measures, it may be possible for healthcare and rehabilitation professionals to measure the patient's performance objectively, thus reducing the inter-rater variability encountered in the conventional assessment. It may also be a component of a complete home-based virtual evaluation process that patients might utilize to extract objective information on their improvement, providing clinicians with valuable input to adapt treatment regimens4. In response to these demands and the rising popularity of telehealth, the development of such VR/AR systems has the potential to serve as an objective clinical assessment tool.
The exploration of virtual BBT started less than a decade ago when Chih-Pin Hsiao et al.19 developed a digital BBT using a depth-sensing camera, an existing wooden box and blocks, and a host computer. They aimed to detect and record hand kinematics data to provide clinicians with additional applications of VR-BBT to the test's score.
Two years later, Cho et al.20 employed non-immersive virtual reality equipment and a depth-sensing sensor to design a VR-BBT to evaluate hand and finger dexterity and validate its efficiency in patients suffering from stroke. Comparing traditional and virtual BBTs demonstrates the viability of converting traditional and unsupervised assessments into a virtual setting. Despite the significant correlations between conventional and VR-BBT in the relative score comparison of affected and non-affected sides, VR-BBT scores were lower than BBT scores. Cho et al. noted that the absence of an actual object is an essential factor that impacts the usability and convenience of virtual reality interactions due to the lack of physical feedback, resulting in different data compared to the real world. Nevertheless, the strong connection between the two assessments is considered significant for their clinical use and subsequent research. However, this approach requires expensive equipment that is not portable and does not accurately visualize the patient's hand,
Ona et al. examined the computerization of the BBT scoring and the automatic administration of the test in 201721 by combining the traditional BBT instrument with the information obtained from a KinectR depth sensor to manage the counting of blocks, as well as acquiring supplementary measurements regarding the subject's movements. They utilized a user interface to allow the clinician to perform the test locally or remotely, retain the collected data, gain access to an up-to-date database structure, and create a report of prior assessments. Their results demonstrated a discrepancy in the number of blocks moved in the real and virtual settings; however, the correlation between the results obtained with the two systems was statistically significant. Additionally, the virtual test's test–retest examination presented a strong and statistically significant correlation. In 2020 Ona et al. proposed a comparable immersive VR implementation on BBT, utilizing controllers, such as the leap motion controller22, to evaluate the hand dexterity of Parkinson's disease patients, demonstrating excellent reliability of the measurements. The same year, Rodríguez et al.23 assessed hand dexterity in spinal cord injury (SCI) patients and showed a Leap Motion Controller-based virtual version of the BBT. A significant correlation was also found between the actual and virtual versions of the test.
In 2022, using an Oculus Quest controller6, Everard et al. created an immersive virtual version of the BBT (VR-BBT) and assessed its validity among post-stroke and healthy individuals. They discovered significant correlations between the BBT and BBT-VR scores, excellent test–retest reliability, and nearly excellent usability. However, they did observe a statistically significant decline in the VR-BBT score with respect to the BBT.
Augmented reality systems can continually record a wide range of valuable data, such as interactive joint ranges of motion and test scores. In AR, the perceived reality is merged with computer-generated material varying from textual representations to animated digital objects. This provides the opportunity to establish quantitative and objective metrics that may be utilized independently and without the presence of a physician. Several tests have been developed to evaluate the upper limb capabilities of stroke survivors, including motor function24 and fine motor skills in a virtual environment22,25. In addition to a personal computer, the aforementioned solutions typically require typically costly devices.
Our study aimed to create an augmented reality-enhanced version of the BBT (AR-BBT) using only a laptop and assess its correlation with the original BBT for stroke patients. The research hypothesis states that stroke patients' AR-BBT and BBT scores will exhibit a positive correlation. Thus, our research team developed an AR-BBT system and compared its efficiency with the conventional test. This evaluation was conducted in a clinical study component aimed at creating a comprehensive platform to enhance hand rehabilitation in individuals suffering from a neurological disease.
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