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Takallou MA, Fallahtafti F, Hassan M, Al-Ramini A, Qolomany B, Pipinos I, Myers S, Alsaleem F. Diagnosis of disease affecting gait with a body acceleration-based model using reflected marker data for training and a wearable accelerometer for implementation. Sci Rep 2024; 14:1075. [PMID: 38212467 PMCID: PMC10784467 DOI: 10.1038/s41598-023-50727-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/21/2023] [Accepted: 12/23/2023] [Indexed: 01/13/2024] Open
Abstract
This paper demonstrates the value of a framework for processing data on body acceleration as a uniquely valuable tool for diagnosing diseases that affect gait early. As a case study, we used this model to identify individuals with peripheral artery disease (PAD) and distinguish them from those without PAD. The framework uses acceleration data extracted from anatomical reflective markers placed in different body locations to train the diagnostic models and a wearable accelerometer carried at the waist for validation. Reflective marker data have been used for decades in studies evaluating and monitoring human gait. They are widely available for many body parts but are obtained in specialized laboratories. On the other hand, wearable accelerometers enable diagnostics outside lab conditions. Models trained by raw marker data at the sacrum achieve an accuracy of 92% in distinguishing PAD patients from non-PAD controls. This accuracy drops to 28% when data from a wearable accelerometer at the waist validate the model. This model was enhanced by using features extracted from the acceleration rather than the raw acceleration, with the marker model accuracy only dropping from 86 to 60% when validated by the wearable accelerometer data.
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Affiliation(s)
- Mohammad Ali Takallou
- Architectural Engineering Department, University of Nebraska-Lincoln, Omaha, NE, 68182, USA
| | - Farahnaz Fallahtafti
- Department of Biomechanics, University of Nebraska at Omaha, Omaha, NE, 6160, USA
- Department of Surgery and VA Research Service, VA Nebraska-Western Iowa Health Care System, Omaha, NE, 68105, USA
| | - Mahdi Hassan
- Department of Biomechanics, University of Nebraska at Omaha, Omaha, NE, 6160, USA
- Department of Surgery and VA Research Service, VA Nebraska-Western Iowa Health Care System, Omaha, NE, 68105, USA
| | - Ali Al-Ramini
- Mechanical Engineering Department, University of Nebraska-Lincoln, Lincoln, NE, 68588, USA
| | - Basheer Qolomany
- Cyber Systems Department, University of Nebraska at Kearney, Kearney, NE, 68849, USA
| | - Iraklis Pipinos
- Department of Surgery and VA Research Service, VA Nebraska-Western Iowa Health Care System, Omaha, NE, 68105, USA
- Department of Surgery, University of Nebraska Medical Center, Omaha, NE, 68105, USA
| | - Sara Myers
- Department of Biomechanics, University of Nebraska at Omaha, Omaha, NE, 6160, USA
- Department of Surgery and VA Research Service, VA Nebraska-Western Iowa Health Care System, Omaha, NE, 68105, USA
| | - Fadi Alsaleem
- Architectural Engineering Department, University of Nebraska-Lincoln, Omaha, NE, 68182, USA.
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