Stroke represents the leading cause of disability in the industrialized world, leading to both motor and cognitive impairments with a strong impact on patients and caregivers’ quality of life (Verheyden et al., 2005; Saban et al., 2010). Post-stroke cognitive disorders can affect different domains, depending on type of stroke and lesion localization, onset time, age and diagnostic tools used (Zucchella et al., 2014). Executive and attentive functions seem to be the most compromised, followed by language disturbances (Nys et al., 2007; Leśniak et al., 2008). In addition, there is agreement about a greater incidence and severity of neuropsychological disorders after cortical strokes than in subcortical ones (Zucchella et al., 2014). In the most severe cases, post-stroke dementia can occur (Pendlebury, 2012). It is noteworthy that these cognitive disturbances adversely affect the rehabilitation process and functional recovery (Cumming et al., 2013; Park et al., 2017). For this reason, it is essential to diagnose them correctly and carry out the adequate cognitive rehabilitation. In recent years, the effectiveness of technology-mediated cognitive rehabilitation systems has emerged. Several studies have found that patients treated with innovative methodologies [i.e. PC-based, virtual reality (VR)] achieved better results than those who performed a traditional rehabilitation (Prokopenko et al., 2013; De Luca et al., 2018). In particular, VR offers a range of potential benefits, including immediate feedback, funny and engaging experience, repeatability, increased motivation and task-oriented exercise. In the last few years, we have witnessed the development of telemedicine, a set of services that overcome the barriers caused by distance, reducing the healthcare costs and encouraging continuity of care (Maresca et al., 2018; Halbert and Bautista, 2019). In the post-stroke acute phase, telemedicine has proved to be a very useful tool for the diagnosis and management of symptoms in emergency departments (Handschu et al., 2003; Geisler et al., 2019). Moreover, its effectiveness on motor recovery after several months from the cerebrovascular event has been demonstrated (Bernocchi et al., 2016; Sarfo et al., 2018). The aim of our study is to evaluate the efficacy of the VR rehabilitation system (VRRS) in improving cognitive function in stroke survivors.
The trial was designed as a pilot, prospective, assessor-blinded, parallel-group study, and was performed at the IRCCS Centro Neurolesi ‘Bonino-Pulejo’ (Messina, Italy).
Forty patients (mean ± SD: age = 55.17 ± 18.37 years; 26% male) admitted to our Institute between June 2017 and December 2018, were enrolled in this study and randomized into either the control (CG: n = 20) or the experimental (EG: n = 20) groups, in order of recruitment. Demographical characteristics of the two groups are reported in Table 1.
Patients were affected by cognitive disorders due to either ischemic or hemorrhagic stroke. Inclusion criteria were: (1) patients in subacute phase (3–6 months after the acute event); (2) absence of severe spasticity; (3) absence of disabling sensory alterations.
Exclusion criteria were: (1) severe paresis of the upper limb (Muscle Research Council < 3); (2) presence of severe psychiatric illness; iii) epileptic seizure non-responding to treatment.
All participants gave informed consent before study participation. Additionally, written informed consent for publication of clinical images was obtained from the participants. This study was conducted in accordance with the 1964 Helsinki Declaration, and approved by our Research Institute Ethics Committee (ID IRCCSME 25/17).
All of the patients were assessed by means of a specific neuropsychological evaluation at baseline (T0), after twelve weeks (T1), and at the end of the protocol, that is 12 weeks later (T2). The neuropsychological battery: (1) Montreal Overall Cognitive Assessment (MOCA) to evaluate the global cognitive level; (2) Frontal Assessment Battery (FAB) and Weigl Test to investigate executive functions; (3) Attentive Matrices (AM) and Trail Making Test (TMT A, B and B-A) to detect attentive processes; (4) Rey Auditory Verbal Learning Test (RAVLT; immediate and differite) and Digit Span to verify memory abilities; (5) phonemic and semantic verbal fluency and (6) Hamilton Rating Scale for Anxiety (HRS-D) and Depression (HRS-D).
The study lasted 6 months and included two phases, each lasting 12 weeks. During the first phase (T0–T1) the two groups underwent different rehabilitative training at our center: the EG patients underwent a cognitive rehabilitation training performed using the VRRS-Evo, whereas the CG patients were trained with the same exercises, but using paper–pencil tools. The EG and the CG performed the same amount of treatment (five sessions a week, each session lasting about 50 minutes). In the second phase (T1-T2), all the patients were discharged, and the EG continued cognitive rehabilitation using the VRRS Home Tablet including the same exercises carried out in inpatient regimen (three sessions a week, each session lasting about 50 minutes). Twice a week, a psychologist monitored the progress of rehabilitation at home through a videoconference. The CG continued the traditional training, with the same amount of treatment.
Virtual reality rehabilitation system
The telerehabilitation device VRRS allows the monitoring of patient remotely in his/her home by a real-time interaction, comparable to a vis-a-vis interaction. The VRRS-Evo can be considered as a ‘central HUB’ to which it is possible to connect, through a USB, a series of specific devices and it is mainly used in a clinical setting (i.e. this is used for inpatients). The VRRS-Tablet, indeed, allows performing the exercises at home, and it is controlled remotely from a workstation, called TeleCockpit (Fig. 1). VRRS has two main categories of exercises. The first category includes 2D exercises, in which the patient interacts with objects and scenarios through the touch screen or a particular magnetic sensor coupled with a button, which emulates mouse interaction. The second one consists of 3D exercises, in which patients interact with 3D virtual scenarios and immersive objects through a magnetic localization sensor generally positioned on the hand (which allows a detection of the final effector’s 3D position). In this study, the cognitive module with 3D scenarios was mainly used during the hospital training, whilst 2D exercises were used at home (Figs. 2 and 3). The exercises performed by the patients included attention, memory, visuo-spatial and reasoning tasks, as described in Table 2.
The cognitive rehabilitation method chosen was the restorative method (consisting in enhancement of compromised abilities) rather than the compensatory (based on the development of alternative strategies).
Data were analyzed using the R version 3.4.0 considering P < 0.05 as statistically significant. The χ2 test was used to compare proportions in categorical variables, whereas the Mann–Whitney U test to compare quantitative variables. Using the lme4 package of R, we performed a linear mixed-effects analysis of the relationship between clinical outcomes and the treatment. Thus, any model included the two-level variable ‘group’ (1 = experimental; 0 = control) and the three-level variable ‘evaluation time’ (T0, T1, T2) as fixed effects, the subject’s variability as random effect, as well as correlated intercepts and slopes for the fixed factors. We also included an interaction term for group and evaluation time. Homoscedasticity was investigated through the Levene test, for both the fixed factors. P values were obtained by likelihood ratio tests of the full model, including the effect ‘treatment’ against the model without this effect. As post-hoc test, pairwise comparisons of all levels by Student’s t-test were computed on the Least Square Means differences adjusted with the Tukey’s test.
Linear mixed effects analysis results showed that the scores of MOCA (χ2(3) = 21.93; P < 0.001), AM (χ2(3) = 19.01; P < 0.001), TMT.B (χ2(3) = 12.80; P < 0.01), TMT.B-A (χ2(3) = 17.80; P < 0.01), Phonemic Fluency (χ2(3) = 17.92; P < 0.001), Semantic Fluency (χ2(3) = 27.69; P < 0.001), RAVL.I (χ2(3) = 15.05; P < 0.01), HRS-A (χ2(3) = 15.68; P < 0.01) and HRS-D (χ2(3) = 37.17; P < 0.001) were affected by the type of the rehabilitative treatment. On the contrary, no effects on TMT.A score were found (χ2(3) = 4.79; P = 0.19), as well as for RAVL.D (χ2(3) = 6.79; P = 0.08), Digit Span (χ2(3) = 5.87; P = 0.12), WEIGL (χ2(3) = 5.62; P = 0.13) and FAB (χ2(3) = 3.06; P = 0.38).
Post-hoc analysis results in Table 3 showed significant differences between the EG and the CG at T2 only for Phonemic Fluency (P = 0.04) and RAVL.I (P = 0.03). For these two tests, as well as for AM, Semantic Fluency and HRS-A, we observed an improvement only in the EG, especially from T1 to T2. Notably, concerning TMT.B we observed an initial worsening (T0–T1) in both the groups, followed by an improvement from T1 to T2 only in the EG (Fig. 4a and b). On the contrary, for MOCA and HRS-D a significant improvement in both the groups we observed throughout the duration of the study. However, the EG scores improved better and more quickly than the ones of the CG, as shown in Fig. 4a and b.
Our evidence shows the effectiveness of telerehabilitation for the treatment of cognitive disorders following stroke. In our study, the patients continue to perform at home the same type of exercises that had been proposed during hospitalization, and were monitored by a therapist ensuring the continuity of the rehabilitative program. This has allowed the strengthening and maintenance of the acquired skills. Moreover, patients perceived constant attention to them and maintained a high level of motivation. This is very important, considering that the main risk of post-stroke rehabilitation (cognitive and motor) is that the recovery achieved in hospital will be lost at home.
Specifically, at the end of the study, we found a more significant improvement in the global cognitive level, as well as in the attentive, memory and linguistic skills in the EG. On the other hand, no substantial differences were found about the executive functions, probably due to the restorative method based on abstract reasoning that we used. In fact, the data in literature (Poulin et al., 2012; Dawson et al., 2013) concerning the rehabilitation of executive functions suggest that the most effective method is the compensatory one, based on the development of alternative strategies through tasks related to everyday life situations.
Patients undergoing VRRS showed a significant decrease in the levels of anxiety, as compared to the CG. Several studies have shown how a telerehabilitation program could have positive effects on emotional state (Dodakian et al., 2017; Maresca et al., 2018).
We believe that an important factor leading to these positive results in the EG is the use of VR that encourages a more active participation and allows longer training sessions. VR allows the user to experience and interact with a computer-generated environment, enhances patients’ motivation and enjoyment (important factors for successful rehabilitation) and may also simulate those activities of daily living that may be too dangerous to perform in real life. Exercises performed in a virtual environment help the patient to develop knowledge of results of the movements (knowledge of results) and knowledge of the quality of the movements (knowledge of performance). During rehabilitation in a virtual environment, the central nervous system receives increased feedback signals (augmented feedback), inducing profound changes in neural plasticity that are responsible for the restoration of motor activity and/or cognitive function.
Previous studies have demonstrated the effectiveness of VR in motor and cognitive recovery (Calabrò et al., 2017; Massetti et al., 2018) as well as in the treatment of anxiety and depression (Zeng et al., 2018) in patients suffering from different neurological disorders, including multiple sclerosis (Maggio et al., 2019). Nevertheless, no study examined the simultaneous use of telemedicine and VR, as in this study by means of the VRRS.Our study has some limitations. The sample examined is quite small and it would be interesting to further investigate whether our findings would be confirmed in larger samples. Moreover, patients’ perception of the instrument’s usefulness (for examples by Psychosocial Impact of Assistive Devices Scales questionnaire) was not detected.
It might also be interesting to investigate the positive repercussions on the distress of caregivers since it is known that cognitive disorders have a negative impact on family members (Camak, 2015; Efi et al., 2017)
However, we consider these results promising for the management of cognitive disorders through a continuity of care that allows the maintenance of the recovery achieved, to reduce the number of admissions at hospital and to improve the patient’s emotional well-being.
Conflicts of interest
There are no conflicts of interest.
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