## 1 Introduction
[15] conducted a task-training for stroke patients using a VR application, demonstrated the validity of the application using the MoCA scale, and determined the application's usability through a questionnaire. From the perspective of the subjects' user experience, questionnaires and interviews are often used to evaluate products by investigating user satisfaction, acceptability, usability, and tolerability. [PERSON] et al. [16] conducted an experiment on VR-based dual task-training with young people and MCI older adults. This ended with questionnaires and semi-structured interviews. This ultimately determined the effectiveness of the VR product for the three aspects of acceptability, usability, and tolerability. These subjective scales are simple and quick to assess, but the influence of the subjects' own conditions (education level, cultural background, emotions, etc. ), the subjects' experience with the scales, and the testing environment can make the scores biased. Therefore, using a qualitative basis, the researcher gradually added objective measures to enhance the accuracy of the measurement. Objective measures oriented towards the cognitive domain focus on functional brain imaging techniques, such as positron emission tomography (PET), electroencephalography (EEG), functional magnetic resonance imaging (fMRI), and functional near-infrared spectroscopy (fNIRS). The fNIRS reflects brain activity by collecting changes in hemoglobin concentration in the brain blood [17], which are judged by changes in the concentration of hemoglobin oxyglobin (HbO) and hemoglobin deoxyglobin (HbR) in the blood. This has a high spatial resolution, low cost and portability, and no noise, and can provide different sensitivities during the experiment depending on the distance between the light source and the detector, obtaining clearer physiological information about brain activity [18]. VR-based cognitive training products, mostly using the movement tasks plus cognitive unfolding,are more suitable for fNIRS intervention, and can be used to make timely and accurate assessment judgments based on objective measurements. The Kinect motion sensor (Microsoft Corporation) provides a markerless, full-body 3D motion-tracker and enables the user to virtually interact with the computer system. It can also record the behavioral characteristics of a person when using their body in a natural way to interact with the game [19]. The Kinect sensor is considered a viable and effective tool for training the physical and cognitive components that simultaneously occur in older adults [20]. One of the major features of VR-based products is their relationship with movement. In this study, the subjects' natural behavioral interaction during the task was recorded with the help of Kinect. This was used to objectively determine the relationship between behavior and cognition. Although some studies have begun to evaluate products focusing on the cognitive and motor perspectives of brain function, many challenges remain. First, cognitive training products are still in their infancy, with a gradually increasing variety of training products appearing in various forms, such as physical and virtual products, and no standard training model. Second, the current assessment of training results produced by these products is not accurate enough, and the assessment tools that are used are not comprehensive. A cognitive assessment based on brain function is the current research trend, and due to the complexity of cognition, different scholars are trying to use richer multi-source data to evaluate cognitive training products, without forming a fixable evaluation system. Third, the training characteristics for MCI elderly are not clear, and targeted training cannot be conducted. Based on the above considerations, this study used fNIRS to identify changes in the brain hemoglobin concentration of test subjects while carrying out activities based on products in the VR environment with the help of the device's multisensory features, combined with the Kinect device.