{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,13]],"date-time":"2026-10-13T20:32:41Z","timestamp":1791923561086,"version":"4.3.4"},"reference-count":67,"publisher":"MDPI AG","issue":"4","license":[{"start":{"date-parts":[[2023,2,8]],"date-time":"2023-02-08T00:00:00Z","timestamp":1675814400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Telefield Charitable Fund","award":["ZH3V"],"award-info":[{"award-number":["ZH3V"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>This paper presents a critical review and comparison of the results of recently published studies in the fields of human\u2013machine interface and the use of sonomyography (SMG) for the control of upper limb prothesis. For this review paper, a combination of the keywords \u201cHuman Machine Interface\u201d, \u201cSonomyography\u201d, \u201cUltrasound\u201d, \u201cUpper Limb Prosthesis\u201d, \u201cArtificial Intelligence\u201d, and \u201cNon-Invasive Sensors\u201d was used to search for articles on Google Scholar and PubMed. Sixty-one articles were found, of which fifty-nine were used in this review. For a comparison of the different ultrasound modes, feature extraction methods, and machine learning algorithms, 16 articles were used. Various modes of ultrasound devices for prosthetic control, various machine learning algorithms for classifying different hand gestures, and various feature extraction methods for increasing the accuracy of artificial intelligence used in their controlling systems are reviewed in this article. The results of the review article show that ultrasound sensing has the potential to be used as a viable human\u2013machine interface in order to control bionic hands with multiple degrees of freedom. Moreover, different hand gestures can be classified by different machine learning algorithms trained with extracted features from collected data with an accuracy of around 95%.<\/jats:p>","DOI":"10.3390\/s23041885","type":"journal-article","created":{"date-parts":[[2023,2,8]],"date-time":"2023-02-08T02:04:16Z","timestamp":1675821856000},"page":"1885","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":29,"title":["Controlling Upper Limb Prostheses Using Sonomyography (SMG): A Review"],"prefix":"10.3390","volume":"23","author":[{"given":"Vaheh","family":"Nazari","sequence":"first","affiliation":[{"name":"Department of Biomedical Engineering, The Hong Kong Polytechnic University, Hong Kong SAR, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3407-9226","authenticated-orcid":false,"given":"Yong-Ping","family":"Zheng","sequence":"additional","affiliation":[{"name":"Department of Biomedical Engineering, The Hong Kong Polytechnic University, Hong Kong SAR, China"},{"name":"Research Institute for Smart Ageing, The Hong Kong Polytechnic University, Hong Kong SAR, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2023,2,8]]},"reference":[{"key":"ref_1","first-page":"1384","article-title":"Task-oriented gaming for transfer to prosthesis use","volume":"24","author":"Bongers","year":"2015","journal-title":"IEEE Trans. Neural Syst. Rehabil. Eng."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"16","DOI":"10.1038\/s41378-019-0127-5","article-title":"An epidermal sEMG tattoo-like patch as a new human\u2013machine interface for patients with loss of voice","volume":"6","author":"Liu","year":"2020","journal-title":"Microsyst. Nanoeng."},{"key":"ref_3","first-page":"150","article-title":"Myoelectric control of artificial limbs\u2014Is there a need to change focus? [In the spotlight]","volume":"29","author":"Jiang","year":"2012","journal-title":"IEEE Signal Process. Mag."},{"key":"ref_4","doi-asserted-by":"crossref","unstructured":"Nazari, V., Pouladian, M., Zheng, Y.-P., and Alam, M. (2021). A Compact and Lightweight Rehabilitative Exoskeleton to Restore Grasping Functions for People with Hand Paralysis. Sensors, 21.","DOI":"10.21203\/rs.3.rs-870815\/v1"},{"key":"ref_5","doi-asserted-by":"crossref","unstructured":"Nazari, V., Pouladian, M., Zheng, Y.-P., and Alam, M. (2021). Compact Design of A Lightweight Rehabilitative Exoskeleton for Restoring Grasping Function in Patients with Hand Paralysis. Res. Sq., Preprits.","DOI":"10.21203\/rs.3.rs-870815\/v1"},{"key":"ref_6","doi-asserted-by":"crossref","unstructured":"Zhang, Y., Yu, C., and Shi, Y. (2018, January 15\u201320). Designing autonomous driving HMI system: Interaction need insight and design tool study. Proceedings of the International Conference on Human-Computer Interaction, Las Vegas, NV, USA.","DOI":"10.1007\/978-3-319-92285-0_58"},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"131","DOI":"10.1109\/THMS.2020.2969380","article-title":"Review of human\u2013machine interfaces for small unmanned systems with robotic manipulators","volume":"50","author":"Young","year":"2020","journal-title":"IEEE Trans. Hum.-Mach. Syst."},{"key":"ref_8","doi-asserted-by":"crossref","unstructured":"Wilde, M., Chan, M., and Kish, B. (2020, January 7\u201314). Predictive human-machine interface for teleoperation of air and space vehicles over time delay. Proceedings of the 2020 IEEE Aerospace Conference, Big Sky, MT, USA.","DOI":"10.1109\/AERO47225.2020.9172297"},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"9438","DOI":"10.1109\/TVT.2019.2933601","article-title":"Building trust in autonomous vehicles: Role of virtual reality driving simulators in HMI design","volume":"68","author":"Morra","year":"2019","journal-title":"IEEE Trans. Veh. Technol."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"54","DOI":"10.1186\/s12984-015-0048-y","article-title":"The H2 robotic exoskeleton for gait rehabilitation after stroke: Early findings from a clinical study","volume":"12","author":"Bortole","year":"2015","journal-title":"J. Neuroeng. Rehabil."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"113","DOI":"10.1109\/TRO.2015.2503726","article-title":"Minimal assist-as-needed controller for upper limb robotic rehabilitation","volume":"32","author":"Pehlivan","year":"2015","journal-title":"IEEE Trans. Robot."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"431","DOI":"10.1109\/TNSRE.2022.3149793","article-title":"Recognizing Continuous Multiple Degrees of Freedom Foot Movements With Inertial Sensors","volume":"30","author":"Zhu","year":"2022","journal-title":"IEEE Trans. Neural Syst. Rehabil. Eng."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"11","DOI":"10.1007\/s41315-019-00086-3","article-title":"Peripheral nerve bionic interface: A review of electrodes","volume":"3","author":"Russell","year":"2019","journal-title":"Int. J. Intell. Robot. Appl."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"43","DOI":"10.1186\/s12984-020-00667-5","article-title":"Interfaces with the peripheral nervous system for the control of a neuroprosthetic limb: A review","volume":"17","author":"Yildiz","year":"2020","journal-title":"J. Neuroeng. Rehabil."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"eabg0656","DOI":"10.1126\/scirobotics.abg0656","article-title":"Magnetomicrometry","volume":"6","author":"Taylor","year":"2021","journal-title":"Sci. Robot."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"11","DOI":"10.3390\/prosthesis3010003","article-title":"Can Prosthetic Hands Mimic a Healthy Human Hand?","volume":"3","author":"Ng","year":"2021","journal-title":"Prosthesis"},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"247","DOI":"10.2147\/MDER.S91102","article-title":"Myoelectric control of prosthetic hands: State-of-the-art review","volume":"9","author":"Geethanjali","year":"2016","journal-title":"Med. Devices Evid. Res."},{"key":"ref_18","doi-asserted-by":"crossref","unstructured":"Mahmood, N.T., Al-Muifraje, M.H., Saeed, T.R., and Kaittan, A.H. (2020, January 9\u201310). Upper prosthetic design based on EMG: A systematic review. Proceedings of the IOP Conference Series: Materials Science and Engineering, Duhok, Iraq.","DOI":"10.1088\/1757-899X\/978\/1\/012025"},{"key":"ref_19","unstructured":"Mohebbian, M.R., Nosouhi, M., Fazilati, F., Esfahani, Z.N., Amiri, G., Malekifar, N., Yusefi, F., Rastegari, M., and Marateb, H.R. (2021). A Comprehensive Review of Myoelectric Prosthesis Control. arXiv."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"43","DOI":"10.1186\/s12984-022-01019-1","article-title":"EMG-driven control in lower limb prostheses: A topic-based systematic review","volume":"19","author":"Cimolato","year":"2022","journal-title":"J. NeuroEngineering Rehabil."},{"key":"ref_21","doi-asserted-by":"crossref","unstructured":"Ortenzi, V., Tarantino, S., Castellini, C., and Cipriani, C. (2015, January 11\u201314). Ultrasound imaging for hand prosthesis control: A comparative study of features and classification methods. Proceedings of the 2015 IEEE International Conference on Rehabilitation Robotics (ICORR), Singapore.","DOI":"10.1109\/ICORR.2015.7281166"},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"884","DOI":"10.1016\/j.ultrasmedbio.2011.03.008","article-title":"A comparative evaluation of sonomyography, electromyography, force, and wrist angle in a discrete tracking task","volume":"37","author":"Guo","year":"2011","journal-title":"Ultrasound Med. Biol."},{"key":"ref_23","doi-asserted-by":"crossref","unstructured":"Ribeiro, J., Mota, F., Cavalcante, T., Nogueira, I., Gondim, V., Albuquerque, V., and Alexandria, A. (2019). Analysis of man-machine interfaces in upper-limb prosthesis: A review. Robotics, 8.","DOI":"10.3390\/robotics8010016"},{"key":"ref_24","unstructured":"Haque, M., and Promon, S.K. (2022). Neural Implants: A Review Of Current Trends And Future Perspectives. Eurpoe PMC, Preprint."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"245","DOI":"10.3109\/03093640409167756","article-title":"The use of targeted muscle reinnervation for improved myoelectric prosthesis control in a bilateral shoulder disarticulation amputee","volume":"28","author":"Kuiken","year":"2004","journal-title":"Prosthet. Orthot. Int."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"2057","DOI":"10.1016\/j.apmr.2008.05.016","article-title":"Control of a six degree of freedom prosthetic arm after targeted muscle reinnervation surgery","volume":"89","author":"Miller","year":"2008","journal-title":"Arch. Phys. Med. Rehabil."},{"key":"ref_27","first-page":"6764","article-title":"Book recommendation platform using deep learning","volume":"7","author":"Wadikar","year":"2020","journal-title":"Int. Res. J. Eng. Technol. IRJET"},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"794","DOI":"10.1111\/ner.12165","article-title":"A fully implanted intramuscular bipolar myoelectric signal recording electrode","volume":"17","author":"Memberg","year":"2014","journal-title":"Neuromodulation Technol. Neural Interface"},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"6","DOI":"10.1186\/s41205-020-00059-4","article-title":"Non-contact visual control of personalized hand prostheses\/exoskeletons by tracking using augmented reality glasses","volume":"6","author":"Hazubski","year":"2020","journal-title":"3D Print. Med."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"1368","DOI":"10.1109\/TBME.2016.2517742","article-title":"Control of a robotic hand using a tongue control system\u2014A prosthesis application","volume":"63","author":"Johansen","year":"2016","journal-title":"IEEE Trans. Biomed. Eng."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"237","DOI":"10.3390\/prosthesis2030020","article-title":"Invasive versus Non-Invasive Neuroprosthetics of the Upper Limb: Which Way to Go?","volume":"2","author":"Otte","year":"2020","journal-title":"Prosthesis"},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"4532","DOI":"10.3390\/s19204532","article-title":"Assisted grasping in individuals with tetraplegia: Improving control through residual muscle contraction and movement","volume":"19","author":"Fonseca","year":"2019","journal-title":"Sensors"},{"key":"ref_33","doi-asserted-by":"crossref","unstructured":"Fang, C., He, B., Wang, Y., Cao, J., and Gao, S. (2020). EMG-centered multisensory based technologies for pattern recognition in rehabilitation: State of the art and challenges. Biosensors, 10.","DOI":"10.3390\/bios10080085"},{"key":"ref_34","doi-asserted-by":"crossref","unstructured":"Briouza, S., Gritli, H., Khraief, N., Belghith, S., and Singh, D. (2021, January 25\u201326). A Brief Overview on Machine Learning in Rehabilitation of the Human Arm via an Exoskeleton Robot. Proceedings of the 2021 International Conference on Data Analytics for Business and Industry (ICDABI), Sakheer, Bahrain.","DOI":"10.1109\/ICDABI53623.2021.9655865"},{"key":"ref_35","doi-asserted-by":"crossref","unstructured":"Zhang, S., Li, Y., Zhang, S., Shahabi, F., Xia, S., Deng, Y., and Alshurafa, N. (2022). Deep learning in human activity recognition with wearable sensors: A review on advances. Sensors, 22.","DOI":"10.3390\/s22041476"},{"key":"ref_36","unstructured":"Zadok, D., Salzman, O., Wolf, A., and Bronstein, A.M. (2022). Towards Predicting Fine Finger Motions from Ultrasound Images via Kinematic Representation. arXiv."},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"5895","DOI":"10.1109\/JSEN.2019.2905243","article-title":"A lightweight ultrasound probe for wearable human\u2013machine interfaces","volume":"19","author":"Yan","year":"2019","journal-title":"IEEE Sens. J."},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"405","DOI":"10.1016\/j.medengphy.2005.07.012","article-title":"Sonomyography: Monitoring morphological changes of forearm muscles in actions with the feasibility for the control of powered prosthesis","volume":"28","author":"Zheng","year":"2006","journal-title":"Med. Eng. Phys."},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"103112","DOI":"10.1016\/j.bspc.2021.103112","article-title":"Wrist and finger motion recognition via M-mode ultrasound signal: A feasibility study","volume":"71","author":"Li","year":"2022","journal-title":"Biomed. Signal Process. Control"},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"9499","DOI":"10.1038\/s41598-019-45459-7","article-title":"Proprioceptive sonomyographic control: A novel method for intuitive and proportional control of multiple degrees-of-freedom for individuals with upper extremity limb loss","volume":"9","author":"Dhawan","year":"2019","journal-title":"Sci. Rep."},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"1277","DOI":"10.1109\/TBME.2018.2872593","article-title":"Wrist and finger gesture recognition with single-element ultrasound signals: A comparison with single-channel surface electromyogram","volume":"66","author":"He","year":"2018","journal-title":"IEEE Trans. Biomed. Eng."},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"494","DOI":"10.3389\/fphys.2014.00494","article-title":"Detection of the electromechanical delay and its components during voluntary isometric contraction of the quadriceps femoris muscle","volume":"5","author":"Begovic","year":"2014","journal-title":"Front. Physiol."},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"42011","DOI":"10.1038\/srep42011","article-title":"Spatial variation and inconsistency between estimates of onset of muscle activation from EMG and ultrasound","volume":"7","author":"Dieterich","year":"2017","journal-title":"Sci. Rep."},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"391","DOI":"10.1016\/j.gaitpost.2013.08.008","article-title":"Detection of the onset of gait initiation using kinematic sensors and EMG in transfemoral amputees","volume":"39","author":"Wentink","year":"2014","journal-title":"Gait Posture"},{"key":"ref_45","doi-asserted-by":"crossref","first-page":"906","DOI":"10.1152\/japplphysiol.00092.2010","article-title":"Dynamic imaging of skeletal muscle contraction in three orthogonal directions","volume":"109","author":"Lopata","year":"2010","journal-title":"J. Appl. Physiol."},{"key":"ref_46","doi-asserted-by":"crossref","first-page":"2505","DOI":"10.1109\/JBHI.2019.2891997","article-title":"Lower limb motion estimation using ultrasound imaging: A framework for assistive device control","volume":"23","author":"Jahanandish","year":"2019","journal-title":"IEEE J. Biomed. Health Inform."},{"key":"ref_47","doi-asserted-by":"crossref","first-page":"187","DOI":"10.1682\/JRRD.2007.02.0026","article-title":"Dynamic monitoring of forearm muscles using one-dimensional sonomyography system","volume":"45","author":"Guo","year":"2008","journal-title":"J. Rehabil. Res. Dev."},{"key":"ref_48","doi-asserted-by":"crossref","first-page":"894","DOI":"10.1016\/j.ultrasmedbio.2008.11.017","article-title":"Performances of one-dimensional sonomyography and surface electromyography in tracking guided patterns of wrist extension","volume":"35","author":"Guo","year":"2009","journal-title":"Ultrasound Med. Biol."},{"key":"ref_49","unstructured":"Guo, J. (2010). One-Dimensional Sonomyography (SMG) for Skeletal Muscle Assessment and Prosthetic Control. [Ph.D. Thesis, Hong Kong Polytechnic University]."},{"key":"ref_50","doi-asserted-by":"crossref","first-page":"1076","DOI":"10.1016\/j.ultrasmedbio.2010.04.015","article-title":"Sonomyography (SMG) control for powered prosthetic hand: A study with normal subjects","volume":"36","author":"Chen","year":"2010","journal-title":"Ultrasound Med. Biol."},{"key":"ref_51","doi-asserted-by":"crossref","first-page":"43","DOI":"10.1177\/0309364612446652","article-title":"Towards the application of one-dimensional sonomyography for powered upper-limb prosthetic control using machine learning models","volume":"37","author":"Guo","year":"2013","journal-title":"Prosthet. Orthot. Int."},{"key":"ref_52","doi-asserted-by":"crossref","first-page":"1199","DOI":"10.1109\/TNSRE.2018.2829913","article-title":"Towards wearable A-mode ultrasound sensing for real-time finger motion recognition","volume":"26","author":"Yang","year":"2018","journal-title":"IEEE Trans. Neural Syst. Rehabil. Eng."},{"key":"ref_53","unstructured":"Szabo, T.L. (2004). Diagnostic Ultrasound Imaging: Inside Out, Academic Press."},{"key":"ref_54","doi-asserted-by":"crossref","first-page":"970","DOI":"10.1109\/TNSRE.2020.2977908","article-title":"Simultaneous prediction of wrist\/hand motion via wearable ultrasound sensing","volume":"28","author":"Yang","year":"2020","journal-title":"IEEE Trans. Neural Syst. Rehabil. Eng."},{"key":"ref_55","unstructured":"Engdahl, S., Mukherjee, B., Akhlaghi, N., Dhawan, A., Bashatah, A., Patwardhan, S., Holley, R., Kaliki, R., Monroe, B., and Sikdar, S. (2020, January 10\u201313). A Novel Method for Achieving Dexterous, Proportional Prosthetic Control using Sonomyography. Proceedings of the MEC20 Symposium, Fredericton, NB, Canada."},{"key":"ref_56","doi-asserted-by":"crossref","first-page":"87","DOI":"10.1682\/JRRD.2009.03.0031","article-title":"Feasibility of controlling prosthetic hand using sonomyography signal in real time: Preliminary study","volume":"47","author":"Shi","year":"2010","journal-title":"J. Rehabil. Res. Dev."},{"key":"ref_57","doi-asserted-by":"crossref","first-page":"1695","DOI":"10.1016\/j.ultrasmedbio.2012.04.021","article-title":"Recognition of finger flexion motion from ultrasound image: A feasibility study","volume":"38","author":"Shi","year":"2012","journal-title":"Ultrasound Med. Biol."},{"key":"ref_58","doi-asserted-by":"crossref","first-page":"1687","DOI":"10.1109\/TBME.2015.2498124","article-title":"Real-time classification of hand motions using ultrasound imaging of forearm muscles","volume":"63","author":"Akhlaghi","year":"2015","journal-title":"IEEE Trans. Biomed. Eng."},{"key":"ref_59","doi-asserted-by":"crossref","unstructured":"McIntosh, J., Marzo, A., Fraser, M., and Phillips, C. (2017, January 6\u201311). Echoflex: Hand gesture recognition using ultrasound imaging. Proceedings of the 2017 CHI Conference on Human Factors in Computing Systems, Denver, CO, USA.","DOI":"10.1145\/3025453.3025807"},{"key":"ref_60","doi-asserted-by":"crossref","first-page":"688","DOI":"10.1109\/TBME.2019.2919488","article-title":"Sparsity analysis of a sonomyographic muscle\u2013computer interface","volume":"67","author":"Akhlaghi","year":"2019","journal-title":"IEEE Trans. Biomed. Eng."},{"key":"ref_61","doi-asserted-by":"crossref","first-page":"24105","DOI":"10.1109\/ACCESS.2021.3056353","article-title":"Evaluation of finger flexion classification at reduced lateral spatial resolutions of ultrasound","volume":"9","author":"Fernandes","year":"2021","journal-title":"IEEE Access"},{"key":"ref_62","doi-asserted-by":"crossref","first-page":"237","DOI":"10.1002\/jmri.23608","article-title":"Diffusion-tensor MRI reveals the complex muscle architecture of the human forearm","volume":"36","author":"Froeling","year":"2012","journal-title":"J. Magn. Reson. Imaging"},{"key":"ref_63","doi-asserted-by":"crossref","unstructured":"Castellini, C., and Passig, G. (2011, January 25\u201330). Ultrasound image features of the wrist are linearly related to finger positions. Proceedings of the 2011 IEEE\/RSJ International Conference on Intelligent Robots and Systems, San Francisco, CA, USA.","DOI":"10.1109\/IROS.2011.6094831"},{"key":"ref_64","doi-asserted-by":"crossref","first-page":"788","DOI":"10.1109\/TNSRE.2012.2207916","article-title":"Using ultrasound images of the forearm to predict finger positions","volume":"20","author":"Castellini","year":"2012","journal-title":"IEEE Trans. Neural Syst. Rehabil. Eng."},{"key":"ref_65","doi-asserted-by":"crossref","first-page":"1395","DOI":"10.1109\/JBHI.2017.2766249","article-title":"Ultrasound-based sensing models for finger motion classification","volume":"22","author":"Huang","year":"2017","journal-title":"IEEE J. Biomed. Health Inform."},{"key":"ref_66","doi-asserted-by":"crossref","unstructured":"Zhou, Y., and Zheng, Y.-P. (2021). Sonomyography: Dynamic and Functional Assessment of Muscle Using Ultrasound Imaging, Springer Nature.","DOI":"10.1007\/978-981-16-7140-1"},{"key":"ref_67","doi-asserted-by":"crossref","first-page":"517","DOI":"10.1126\/science.abo2542","article-title":"Bioadhesive ultrasound for long-term continuous imaging of diverse organs","volume":"377","author":"Wang","year":"2022","journal-title":"Science"}],"container-title":["Sensors"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1424-8220\/23\/4\/1885\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T18:27:33Z","timestamp":1760120853000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1424-8220\/23\/4\/1885"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,2,8]]},"references-count":67,"journal-issue":{"issue":"4","published-online":{"date-parts":[[2023,2]]}},"alternative-id":["s23041885"],"URL":"https:\/\/doi.org\/10.3390\/s23041885","relation":{"has-preprint":[{"id-type":"doi","id":"10.20944\/preprints202301.0384.v1","asserted-by":"object"}]},"ISSN":["1424-8220"],"issn-type":[{"value":"1424-8220","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023,2,8]]}}}