A Speech-Based Mobile Screening Tool for Mild Cognitive Impairment: Technical Performance and User Engagement Evaluation
Traditional screening methods for Mild Cognitive Impairment (MCI) face limitations in accessibility and scalability. To address this, we developed and validated a speech-based automatic screening app implementing three speech–language tasks with user-centered design and server–client architecture. T...
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MDPI AG
2025-01-01
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| Series: | Bioengineering |
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| Online Access: | https://www.mdpi.com/2306-5354/12/2/108 |
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| author | Rukiye Ruzi Yue Pan Menwa Lawrence Ng Rongfeng Su Lan Wang Jianwu Dang Liwei Liu Nan Yan |
| author_facet | Rukiye Ruzi Yue Pan Menwa Lawrence Ng Rongfeng Su Lan Wang Jianwu Dang Liwei Liu Nan Yan |
| author_sort | Rukiye Ruzi |
| collection | DOAJ |
| description | Traditional screening methods for Mild Cognitive Impairment (MCI) face limitations in accessibility and scalability. To address this, we developed and validated a speech-based automatic screening app implementing three speech–language tasks with user-centered design and server–client architecture. The app integrates automated speech processing and SVM classifiers for MCI detection. Functionality validation included comparison with manual assessment and testing in real-world settings (<i>n</i> = 12), with user engagement evaluated separately (<i>n</i> = 22). The app showed comparable performance with manual assessment (F1 = 0.93 vs. 0.95) and maintained reliability in real-world settings (F1 = 0.86). Task engagement significantly influenced speech patterns: users rating tasks as “most interesting” produced more speech content (<i>p</i> < 0.05), though behavioral observations showed consistent cognitive processing across perception groups. User engagement analysis revealed high technology acceptance (86%) across educational backgrounds, with daily cognitive exercise habits significantly predicting task benefit perception (H = 9.385, <i>p</i> < 0.01). Notably, perceived task difficulty showed no significant correlation with cognitive performance (<i>p</i> = 0.119), suggesting the system’s accessibility to users of varying abilities. While preliminary, the mobile app demonstrated both robust assessment capabilities and sustained user engagement, suggesting the potential viability of widespread cognitive screening in the geriatric population. |
| format | Article |
| id | doaj-art-79093ebece0342418f3b77d6be897f15 |
| institution | DOAJ |
| issn | 2306-5354 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | MDPI AG |
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| series | Bioengineering |
| spelling | doaj-art-79093ebece0342418f3b77d6be897f152025-08-20T02:44:40ZengMDPI AGBioengineering2306-53542025-01-0112210810.3390/bioengineering12020108A Speech-Based Mobile Screening Tool for Mild Cognitive Impairment: Technical Performance and User Engagement EvaluationRukiye Ruzi0Yue Pan1Menwa Lawrence Ng2Rongfeng Su3Lan Wang4Jianwu Dang5Liwei Liu6Nan Yan7Guangdong-Hong Kong-Macao Joint Laboratory of Human–Machine Intelligence-Synergy Systems, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, ChinaAdvanced Computing and Storage Laboratory, Central Research Institute, 2012 Laboratories, Huawei Technologies Co., Ltd., Nanjing 210012, ChinaSpeech Science Laboratory, Faculty of Education, University of Hong Kong, Hong Kong SAR, ChinaGuangdong-Hong Kong-Macao Joint Laboratory of Human–Machine Intelligence-Synergy Systems, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, ChinaGuangdong-Hong Kong-Macao Joint Laboratory of Human–Machine Intelligence-Synergy Systems, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, ChinaGuangdong-Hong Kong-Macao Joint Laboratory of Human–Machine Intelligence-Synergy Systems, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, ChinaAdvanced Computing and Storage Laboratory, Central Research Institute, 2012 Laboratories, Huawei Technologies Co., Ltd., Nanjing 210012, ChinaGuangdong-Hong Kong-Macao Joint Laboratory of Human–Machine Intelligence-Synergy Systems, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, ChinaTraditional screening methods for Mild Cognitive Impairment (MCI) face limitations in accessibility and scalability. To address this, we developed and validated a speech-based automatic screening app implementing three speech–language tasks with user-centered design and server–client architecture. The app integrates automated speech processing and SVM classifiers for MCI detection. Functionality validation included comparison with manual assessment and testing in real-world settings (<i>n</i> = 12), with user engagement evaluated separately (<i>n</i> = 22). The app showed comparable performance with manual assessment (F1 = 0.93 vs. 0.95) and maintained reliability in real-world settings (F1 = 0.86). Task engagement significantly influenced speech patterns: users rating tasks as “most interesting” produced more speech content (<i>p</i> < 0.05), though behavioral observations showed consistent cognitive processing across perception groups. User engagement analysis revealed high technology acceptance (86%) across educational backgrounds, with daily cognitive exercise habits significantly predicting task benefit perception (H = 9.385, <i>p</i> < 0.01). Notably, perceived task difficulty showed no significant correlation with cognitive performance (<i>p</i> = 0.119), suggesting the system’s accessibility to users of varying abilities. While preliminary, the mobile app demonstrated both robust assessment capabilities and sustained user engagement, suggesting the potential viability of widespread cognitive screening in the geriatric population.https://www.mdpi.com/2306-5354/12/2/108mobile health applicationsmild cognitive impairmentMCI detectionautomatic screeninguser engagement |
| spellingShingle | Rukiye Ruzi Yue Pan Menwa Lawrence Ng Rongfeng Su Lan Wang Jianwu Dang Liwei Liu Nan Yan A Speech-Based Mobile Screening Tool for Mild Cognitive Impairment: Technical Performance and User Engagement Evaluation Bioengineering mobile health applications mild cognitive impairment MCI detection automatic screening user engagement |
| title | A Speech-Based Mobile Screening Tool for Mild Cognitive Impairment: Technical Performance and User Engagement Evaluation |
| title_full | A Speech-Based Mobile Screening Tool for Mild Cognitive Impairment: Technical Performance and User Engagement Evaluation |
| title_fullStr | A Speech-Based Mobile Screening Tool for Mild Cognitive Impairment: Technical Performance and User Engagement Evaluation |
| title_full_unstemmed | A Speech-Based Mobile Screening Tool for Mild Cognitive Impairment: Technical Performance and User Engagement Evaluation |
| title_short | A Speech-Based Mobile Screening Tool for Mild Cognitive Impairment: Technical Performance and User Engagement Evaluation |
| title_sort | speech based mobile screening tool for mild cognitive impairment technical performance and user engagement evaluation |
| topic | mobile health applications mild cognitive impairment MCI detection automatic screening user engagement |
| url | https://www.mdpi.com/2306-5354/12/2/108 |
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