**4. Conclusions**

This paper presented the analysis and comparison of a markerless camera-based system for elbow angles assessment. The proposed markerless system uses two RGB-D cameras to reduce errors and inaccuracies related to self-occlusion issues. The non-wearable system performance was compared with two wearable solutions, namely POF curvature sensor and IMUs, in flexion/extension movements performed in different planes (sagittal, transverse, and frontal planes). Even though the proposed markerless camera-based system showed lower errors than some similar systems proposed in the literature, the errors are still high for movement analysis applications. To tackle this limitation, a comprehensive analysis of the system showed that despite the high errors, the markerless camera-based system response has a high correlation with the response of the wearable sensors. This also indicated the possibility of applying post-processing techniques aimed at error reduction in those systems. Thus, a compensation technique based on anthropometric measurements of the subjects was proposed and validated using the POF curvature sensor measures, resulting in a significant decrease of the RMSE.

The proposed RGB-D vision system and the novel compensation technique proposed here indicate the suitability of the system on the movement analysis, since the mean error obtained is about 4◦ for the angles tested, i.e., up to 120◦ in the sagittal plane, which is in agreemen<sup>t</sup> with the errors obtained in some sensing approaches for movement analysis [42]. Thus, this work can pave the way for movement analysis applications with markerless camera-based system. Future works include the further investigation of this technique in the other motion planes (frontal and transverse plane) and also in 3D movement scenarios. In addition, further evaluation and new sensor fusion techniques of markerless camera-based systems and optical fiber sensors will also be developed. Currently, to decrease the error, this work can be understood as the foundation of such developments.

**Author Contributions:** N.V.-J., L.V.-V., P.C.-R. implemented the assessment protocol and perform all the tests. N.V.-J., L.A., A.A.R.-D., M.L. implemented the RGB-D system proposed, analyzed the data, contributed in paper writing and revisions. A.L.-J. implemented the proposed POF curvature sensor system, analyzed the data, conceived and implemented the angle correction technique, contributed in paper writing and revisions. L.V.-V., P.C.-R. implemented the IMUs system proposed, contributed in paper writing and revisions. C.M., A.F., T.B. assisted in careful reviewing of the paper and proposed various refinements to the draft proposal made.

**Funding:** This research is financed by CAPES (88887.095626/2015-01)—financing code 001, FAPES (72982608), CNPq (304192/2016-3) and Innovaccion Cauca Research Project-02-2014 Doctorados Nacionales. This research is also financed by FCT through the program UID/EEA/50008/2019 by the National Funds through the Fundação para a Ciência e a Tecnologia / Ministério da Educação e Ciência, and the European Regional Development Fund under the PT2020 Partnership Agreement. This work is also funded by national funds (OE), through FCT – Fundação para a Ciência e a Tecnologia, I.P., in the scope of the framework contract foreseen in the numbers 4, 5 and 6 of the article 23, of the Decree-Law 57/2016, of August 29, changed by Law 57/2017, of July 19

**Conflicts of Interest:** The authors declare no conflict of interest.
