Key result
Game performance during serious games achieved 83.33% accuracy in classifying mild cognitive impairment among elderly subjects, compared to 68.75% using heart rate variability features.
Why the study?
Cognitive decline is a major concern in the elderly, and although evidence links cognition to the autonomic nervous system via heart rate variability, changes in the autonomic nervous system during serious games remained to be explored.
Can HRV and game performance during serious games detect mild cognitive impairment in elderly subjects?
Cross-Sectional (n=48)
Can HRV and game performance during serious games detect mild cognitive impairment in elderly subjects?
Game performance during serious games may support MCI detection in elderly; hypothesis-generating and requires prospective validation before any clinical adoption.
Cognitive decline is one of the primary concerns in the elderly population. Serious games have been used for different purposes related to elderly care, such as physical therapy, cognitive training and mood management. There has been scientific evidence regarding the relationship between cognition and the autonomic nervous system (ANS) through heart rate variability (HRV). This paper explores the changes in the ANS among elderly people of normal and impaired cognition through measured HRV. Forty-eight subjects were classified into two groups: normal cognition (NC) (n = 24) and mild cognitive impairment (MCI) (n = 24). The subjects went through the following experiment flow: rest for 3 min (Rest 1), play a cognitive aptitude game (Game 1), rest for another 3 min (Rest 2), then play two reaction-time games (Game 2&3). Ten HRV features were extracted from measured electrocardiography (ECG) signals. Based on statistical analysis, there was no significant difference on the HRV between the two groups, but the experiment sessions do have a significant effect. There was no significant interaction between sessions and cognitive status. This implies that the HRV between the two groups have no significant difference, and they will experience similar changes in their HRV regardless of their cognitive status. Based on the game performance, there was a significant difference between the two groups of elderly people. Tree-based pipeline optimization tool (TPOT) was used for generating a machine learning pipeline for classification. Classification accuracy of 68.75% was achieved using HRV features, but higher accuracies of 83.33% and 81.20% were achieved using game performance or both HRV and game performance features, respectively. These results show that HRV has the potential to be used for detection of mild cognition impairment, but game performance can yield better accuracy. Thus, serious games have the potential to be used for assessing cognitive decline among the elderly.
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Hou et al. (2022) conducted a cross-sectional in Mild cognitive impairment (n=48). Mild cognitive impairment vs. Normal cognition was evaluated on Classification accuracy for mild cognitive impairment. Game performance during serious games achieved 83.33% accuracy in classifying mild cognitive impairment among elderly subjects, compared to 68.75% using heart rate variability features.
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