Healthy right-handed subjects aged over 18 years without any neurological disorder or musculoskeletal impairment were recruited from universities and local communities. Patients with chronic stroke were recruited from a rehabilitation unit in Beijing, China. The patient inclusion criteria were as follows: 1) received a stroke diagnosis at least three months earlier confirmed by brain CT or MRI findings, 2) was aged older than 18 years, 3) was right handed with an affected right hand, 4) could sit steadily on a chair without armrest support, 5) was able to move 3 blocks in the BBT within one minute, and 6) understood the whole experimental procedure. The exclusion criteria were as follows: 1) unstable fracture of the upper extremity on the hemiplegic side; 2) spatial or visual disorders, such as visual neglect; 3) epilepsy caused by visual stimuli (lights, television, etc.) in the previous six months; and 4) dizziness in the VR environment. All subjects were given written and verbal information on the current study. A signed informed consent statement was received from each subject. This study adhered to the tenets of the Declaration of Helsinki, and ethical approval was approved by Beihang University (BM20180017).
Apparatus and program
A haptic feedback device (Omega.7, Force Dimension Inc., Switzerland; Fig. 1a) was used to provide interactive forces, including grasping force and block activity. The haptic device allowed a translating force of 12.0 N and grasping force of 8.0 N, as well as an operating space of Φ160 × 110 mm for translation and 240°×140°×180° for rotation. A VR headset (Oculus Rift, Facebook Inc., US) was used to provide a 3D virtual environment that allowed spatial visualization and operation. An open source software library Chai3D combined with the OpenGL library was used to render visualization and haptic interaction in the VBBT program.
A virtual test box with a barrier partition in the middle was created in the VR environment (Fig. 1b). The block was created, one by one, in the compartment of the box on the side of the tested hand. In the case of the VBBT, when a subject had completed one trial in which a block was moved from one compartment to the other, another block was then automatically created (Supplementary Video). This was designed to provide movement consistency and avoid obstructions to the target block by other blocks during grasping. Each block was attributed physical properties, including tactile contact and gravity. A virtual grasping tool was attached to the handle of a haptic device. As a subject moved the handle in the real environment, the virtual tool synchronously performed the same motion in the virtual environment. When contact occurred between the tool and a block, haptic interactions were computed through force rendering algorithms. During the interaction, a haptic thread was created to compute the resulting forces between the virtual tool and block, providing a sense of haptic interaction for the subjects (Fig. 1c).
In the VBBT, some kinematic parameters can be collected by the haptic device to evaluate specific UE motor function in detail. Originally, the haptic device collected the position and velocity of virtual objects, as well as the grasping force of the virtual tool (Fig. 1c). Considering previously validated parameters for UE assessment in the literature [28, 34, 35], the kinematic parameters used in the VBBT were determined and included the following:
1) NZC-ACC: The number of zero-crossings of the moving acceleration in a block transfer, which was used to assess the smoothness and coordination of UE movement.
2) NZC-DRF: The number of zero-crossings of the derivative of the releasing force, which was used to assess hand dexterity.
3) PLR: The ratio of the path length and linear length in a block transfer trial, which was used to assess the efficiency of UE movement.
4) DDP: The distance between the barrier partition and the drop position of a block, which was used to present the efficiency of UE movement.
For the healthy subjects, they were asked to perform the BBT and VBBT, respectively. The BBT was performed according to previously published instructions . In the VBBT, the subjects were seated on a standard height chair facing the haptic device that was placed at their middle line. We first introduced the operation of the haptic device to the subjects until they understood how to use it in the experiment. In the familiarization session of the VBBT, the subjects, wearing the VR headset, were instructed to move the blocks to the opposite compartment until they became fully familiarized with how to operate the haptic device to interact with virtual objects in a VR environment. In the formal session of the VBBT, the subjects were given one minute to move as many blocks as possible until the program automatically stopped. Four weeks after the first experimental session, the healthy subjects were asked to perform the BBT and VBBT again as a retest.
For the patients, they were also asked to perform several widely used assessment scales of UE motor function and cognitive function, including the BBT, ARAT, FMA-UE, Brunnstrom and Mini-Mental State Examination (MMSE). All assessments were performed according to the standard instructions reported in previous studies [11, 31, 36–38]. Then, the patients were asked to perform the VBBT with the same procedures as the healthy subjects. Adequate rest was provided for the patients when they felt tired during the performance. Specially, the test was immediately stopped once the patients felt uncomfortable. When the patients finished the VBBT, they were given a questionnaire to evaluate their subjective preferences for the BBT and VBBT, and an informal interview was conducted regarding their preference. There were 7 questions corresponding to 7 items in the questionnaire, including difference, understandability, enjoyment, attraction, relaxation, effort and tiredness. The patients gave scores (from 1 to 7) to show how true each question was for both the BBT and VBBT, in which 1 indicated “not at all true” and 7 indicated “very true”. The questions in the questionnaire were as follows:
Q1: I don't think there is a significant difference between the BBT and VBBT. (Difference)
Q2: I think the BBT/VBBT is quite easy to understand. (Understandability)
Q3: I enjoy to perform BBT/VBBT very much. (Enjoyment)
Q4: I think the BBT/VBBT can hold my attention very well. (Attraction)
Q5: I feel very relaxed in performing the BBT/VBBT. (Relaxation)
Q6: I put a lot of effort into the BBT/VBBT. (Effort)
Q7: I feel very tired after the BBT/VBBT. (Tiredness)
A demographic analysis was performed with both the healthy and patient subjects. We divided the subjects into three groups according to their ages: the young group, 18–44 years; the middle-aged group, 45–59 years; and the senior group, 60 years or older. A regression analysis was performed between the age and the quantitative performances(N-TB) in both BBT and VBBT. The kinematic parameters (NZC-ACC, NZC-DRF, PLR, and DDP) were compared between the healthy and patient subjects. We determined a normative range by 95% confidence interval (CI) for 2-sided measurements (2.5%-97.5%) of healthy-subject performances for each kinematic parameter. Specific deficiencies in a patient’s motor function were identified when the patient’s measurements fell outside of the normative ranges. A Correlation analysis was conducted between the parameters collected in the BBT (N-BT) as well as the VBBT (N-BT, NZC-ACC, NZC-DRF, PLR, and DDP) and the clinical scales, such as FMA-UE and ARAT for concurrent validity. Spearman rank correlation coefficient was used for the classification : 0.20 or below, little if any correlation; 0.20–0.40, weak correlation; 0.40–0.70, moderate correlation; and 0.70-1.0, strong correlation. A intraclass correlation coefficient (ICC) was used to examine the test-retest reliability of BBT and VBBT [40, 41]: 0.5 or below, poor reliability; 0.50–0.75, moderate reliability; 0.75–0.9, good reliability; and 0.9-1.0, excellent reliability. SPSS version 22.0 (SPSS Inc, Chicago, Illinois) was used to analyse all the data.