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Background Stroke remains one of the major chronic illnesses worldwide that health care organizations will need to address for the next several decades. Individuals poststroke are subject to levels of cognitive impairment and mental health problems. Virtual reality (VR)-based therapies are new technologies used for cognitive rehabilitation and the management of psychological outcomes. Objective This study performed a meta-analysis to evaluate the effects of VR-based therapies on cognitive function and mental health in patients with stroke. Methods A comprehensive database search was performed using PubMed, MEDLINE (Ovid), Embase, Cochrane Library, and APA PsycINFO databases for randomized controlled trials (RCTs) that studied the effects of VR on patients with stroke. We included trials published up to April 15, 2021, that fulfilled our inclusion and exclusion criteria. The literature was screened, data were extracted, and the methodological quality of the included trials was assessed. Meta-analysis was performed using RevMan 5.3 software. Results A total of 894 patients from 23 RCTs were included in our meta-analysis. Compared to traditional rehabilitation therapies, the executive function (standard mean difference [SMD]=0.88, 95% confidence interval [CI]=0.06-1.70, P=.03), memory (SMD=1.44, 95% CI=0.21-2.68, P=.02), and visuospatial function (SMD=0.78, 95% CI=0.23-1.33, P=.006) significantly improved among patients after VR intervention. However, there were no significant differences observed in global cognitive function, attention, verbal fluency, depression, and the quality of life (QoL). Conclusions The findings of our meta-analysis showed that VR-based therapies are efficacious in improving executive function, memory, and visuospatial function in patients with stroke. For global cognitive function, attention, verbal fluency, depression, and the QoL, further research is required. Trial Registration PROSPERO International Prospective Register of Systematic Reviews CRD42021252788; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=252788

In wireless sensor networks, users sometimes need to retrieve real-time data directly from the sensor nodes. Many authentication protocols are proposed to address the security and privacy aspects of this scenario. However, these protocols still have security loopholes and fail to provide strong user anonymity. In order to overcome these shortcomings, we propose an anonymous authenticated key exchange protocol based on Elliptic Curves Cryptography (ECC). The novel protocol provides strong user anonymity such that even the gateway node and the sensor nodes do not know the real identity of the user. The security of the proposed protocol is conducted in a well-defined security model under the CDH assumption. Compared with other related protocols, our protocol is efficient in terms of communication and enjoys stronger security. The only disadvantage is that our protocol consumes more computation resources due to the usage of asymmetric cryptography mechanisms to realize strong anonymity. Consequently, our protocol is suitable for applications which require strong anonymity and high security in wireless sensor networks.

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