Development of Neurodegenerative Disease Diagnosis and Monitoring from Traditional to Digital Biomarkers
Monitoring and assessing the progression of symptoms in neurodegenerative diseases, including Alzheimer’s and Parkinson’s disease, are critical for improving patient outcomes. Traditional biomarkers, such as cerebrospinal fluid analysis and brain imaging, are widely used to investigate the underlyin...
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| Format: | Article |
| Language: | English |
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MDPI AG
2025-02-01
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| Series: | Biosensors |
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| Online Access: | https://www.mdpi.com/2079-6374/15/2/102 |
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| author | Jaeyoon Song Eunseo Cho Huiseop Lee Suyoung Lee Sehyeon Kim Jinsik Kim |
| author_facet | Jaeyoon Song Eunseo Cho Huiseop Lee Suyoung Lee Sehyeon Kim Jinsik Kim |
| author_sort | Jaeyoon Song |
| collection | DOAJ |
| description | Monitoring and assessing the progression of symptoms in neurodegenerative diseases, including Alzheimer’s and Parkinson’s disease, are critical for improving patient outcomes. Traditional biomarkers, such as cerebrospinal fluid analysis and brain imaging, are widely used to investigate the underlying mechanisms of disease and enable early diagnosis. In contrast, digital biomarkers derived from phenotypic changes—such as EEG, eye movement, gait, and speech analysis—offer a noninvasive and accessible alternative. Leveraging portable and widely available devices, such as smartphones and wearable sensors, digital biomarkers are emerging as a promising tool for ND diagnosis and monitoring. This review highlights the comprehensive developments in digital biomarkers, emphasizing their unique advantages and integration potential alongside traditional biomarkers. |
| format | Article |
| id | doaj-art-b20a2cab5a844ccabf492acd17af6d75 |
| institution | DOAJ |
| issn | 2079-6374 |
| language | English |
| publishDate | 2025-02-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Biosensors |
| spelling | doaj-art-b20a2cab5a844ccabf492acd17af6d752025-08-20T02:44:52ZengMDPI AGBiosensors2079-63742025-02-0115210210.3390/bios15020102Development of Neurodegenerative Disease Diagnosis and Monitoring from Traditional to Digital BiomarkersJaeyoon Song0Eunseo Cho1Huiseop Lee2Suyoung Lee3Sehyeon Kim4Jinsik Kim5Department of Biomedical Engineering, College of Life Science and Biotechnology, Dongguk University, Seoul 04620, Republic of KoreaDepartment of Biomedical Engineering, College of Life Science and Biotechnology, Dongguk University, Seoul 04620, Republic of KoreaDepartment of Biomedical Engineering, College of Life Science and Biotechnology, Dongguk University, Seoul 04620, Republic of KoreaDepartment of Biomedical Engineering, College of Life Science and Biotechnology, Dongguk University, Seoul 04620, Republic of KoreaDepartment of Biomedical Engineering, College of Life Science and Biotechnology, Dongguk University, Seoul 04620, Republic of KoreaDepartment of Biomedical Engineering, College of Life Science and Biotechnology, Dongguk University, Seoul 04620, Republic of KoreaMonitoring and assessing the progression of symptoms in neurodegenerative diseases, including Alzheimer’s and Parkinson’s disease, are critical for improving patient outcomes. Traditional biomarkers, such as cerebrospinal fluid analysis and brain imaging, are widely used to investigate the underlying mechanisms of disease and enable early diagnosis. In contrast, digital biomarkers derived from phenotypic changes—such as EEG, eye movement, gait, and speech analysis—offer a noninvasive and accessible alternative. Leveraging portable and widely available devices, such as smartphones and wearable sensors, digital biomarkers are emerging as a promising tool for ND diagnosis and monitoring. This review highlights the comprehensive developments in digital biomarkers, emphasizing their unique advantages and integration potential alongside traditional biomarkers.https://www.mdpi.com/2079-6374/15/2/102digital biomarkerneurodegenerative diseasetraditional biomarkermonitoringpoint of care |
| spellingShingle | Jaeyoon Song Eunseo Cho Huiseop Lee Suyoung Lee Sehyeon Kim Jinsik Kim Development of Neurodegenerative Disease Diagnosis and Monitoring from Traditional to Digital Biomarkers Biosensors digital biomarker neurodegenerative disease traditional biomarker monitoring point of care |
| title | Development of Neurodegenerative Disease Diagnosis and Monitoring from Traditional to Digital Biomarkers |
| title_full | Development of Neurodegenerative Disease Diagnosis and Monitoring from Traditional to Digital Biomarkers |
| title_fullStr | Development of Neurodegenerative Disease Diagnosis and Monitoring from Traditional to Digital Biomarkers |
| title_full_unstemmed | Development of Neurodegenerative Disease Diagnosis and Monitoring from Traditional to Digital Biomarkers |
| title_short | Development of Neurodegenerative Disease Diagnosis and Monitoring from Traditional to Digital Biomarkers |
| title_sort | development of neurodegenerative disease diagnosis and monitoring from traditional to digital biomarkers |
| topic | digital biomarker neurodegenerative disease traditional biomarker monitoring point of care |
| url | https://www.mdpi.com/2079-6374/15/2/102 |
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