{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,22]],"date-time":"2026-01-22T11:47:10Z","timestamp":1769082430789,"version":"3.49.0"},"reference-count":69,"publisher":"MDPI AG","issue":"18","license":[{"start":{"date-parts":[[2021,9,21]],"date-time":"2021-09-21T00:00:00Z","timestamp":1632182400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100002347","name":"Bundesministerium f\u00fcr Bildung und Forschung","doi-asserted-by":"publisher","award":["16SV7115; 03IHS075B"],"award-info":[{"award-number":["16SV7115; 03IHS075B"]}],"id":[{"id":"10.13039\/501100002347","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Clinical classification models are mostly pathology-dependent and, thus, are only able to detect pathologies they have been trained for. Research is needed regarding pathology-independent classifiers and their interpretation. Hence, our aim is to develop a pathology-independent classifier that provides prediction probabilities and explanations of the classification decisions. Spinal posture data of healthy subjects and various pathologies (back pain, spinal fusion, osteoarthritis), as well as synthetic data, were used for modeling. A one-class support vector machine was used as a pathology-independent classifier. The outputs were transformed into a probability distribution according to Platt\u2019s method. Interpretation was performed using the explainable artificial intelligence tool Local Interpretable Model-Agnostic Explanations. The results were compared with those obtained by commonly used binary classification approaches. The best classification results were obtained for subjects with a spinal fusion. Subjects with back pain were especially challenging to distinguish from the healthy reference group. The proposed method proved useful for the interpretation of the predictions. No clear inferiority of the proposed approach compared to commonly used binary classifiers was demonstrated. The application of dynamic spinal data seems important for future works. The proposed approach could be useful to provide an objective orientation and to individually adapt and monitor therapy measures pre- and post-operatively.<\/jats:p>","DOI":"10.3390\/s21186323","type":"journal-article","created":{"date-parts":[[2021,9,21]],"date-time":"2021-09-21T22:35:20Z","timestamp":1632263720000},"page":"6323","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":39,"title":["Classification and Automated Interpretation of Spinal Posture Data Using a Pathology-Independent Classifier and Explainable Artificial Intelligence (XAI)"],"prefix":"10.3390","volume":"21","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-0378-8481","authenticated-orcid":false,"given":"Carlo","family":"Dindorf","sequence":"first","affiliation":[{"name":"Department of Sports Science, Technische Universit\u00e4t Kaiserslautern, 67663 Kaiserslautern, Germany"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2297-3482","authenticated-orcid":false,"given":"J\u00fcrgen","family":"Konradi","sequence":"additional","affiliation":[{"name":"Institute of Physical Therapy, Prevention and Rehabilitation, University Medical Centre, Johannes Gutenberg University Mainz, 55122 Mainz, Germany"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8134-2664","authenticated-orcid":false,"given":"Claudia","family":"Wolf","sequence":"additional","affiliation":[{"name":"Institute of Physical Therapy, Prevention and Rehabilitation, University Medical Centre, Johannes Gutenberg University Mainz, 55122 Mainz, Germany"}]},{"given":"Bertram","family":"Taetz","sequence":"additional","affiliation":[{"name":"Department Augmented Vision, German Research Center for Artificial Intelligence, 67663 Kaiserslautern, Germany"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7283-8166","authenticated-orcid":false,"given":"Gabriele","family":"Bleser","sequence":"additional","affiliation":[{"name":"Department Augmented Vision, German Research Center for Artificial Intelligence, 67663 Kaiserslautern, Germany"}]},{"given":"Janine","family":"Huthwelker","sequence":"additional","affiliation":[{"name":"Institute of Physical Therapy, Prevention and Rehabilitation, University Medical Centre, Johannes Gutenberg University Mainz, 55122 Mainz, Germany"}]},{"given":"Friederike","family":"Werthmann","sequence":"additional","affiliation":[{"name":"Department of Orthopedics and Trauma Surgery, University Medical Centre, Johannes Gutenberg University Mainz, 55122 Mainz, Germany"}]},{"given":"Eva","family":"Bartaguiz","sequence":"additional","affiliation":[{"name":"Department of Sports Science, Technische Universit\u00e4t Kaiserslautern, 67663 Kaiserslautern, Germany"}]},{"given":"Johanna","family":"Kniepert","sequence":"additional","affiliation":[{"name":"Department of Orthopedics and Trauma Surgery, University Medical Centre, Johannes Gutenberg University Mainz, 55122 Mainz, Germany"}]},{"given":"Philipp","family":"Drees","sequence":"additional","affiliation":[{"name":"Department of Orthopedics and Trauma Surgery, University Medical Centre, Johannes Gutenberg University Mainz, 55122 Mainz, Germany"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2157-4287","authenticated-orcid":false,"given":"Ulrich","family":"Betz","sequence":"additional","affiliation":[{"name":"Institute of Physical Therapy, Prevention and Rehabilitation, University Medical Centre, Johannes Gutenberg University Mainz, 55122 Mainz, Germany"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1982-6374","authenticated-orcid":false,"given":"Michael","family":"Fr\u00f6hlich","sequence":"additional","affiliation":[{"name":"Department of Sports Science, Technische Universit\u00e4t Kaiserslautern, 67663 Kaiserslautern, Germany"}]}],"member":"1968","published-online":{"date-parts":[[2021,9,21]]},"reference":[{"key":"ref_1","unstructured":"Robert Koch Institut (2015). 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