## 5 Conclusions  
The paper presents the NeuroPredict platform and one of the algorithms integrated into the platform, an emotion recognition algorithm based on voice features. NeuroPredict, which merges AI and digital health tools for enhanced care of patients with neurodegenerative \begin{table}
\begin{tabular}{c c c c} \hline \hline  & **Precision** & **Recall** & **F1 Score** \\ \hline \multirow{3}{*}{Class} & Positive & 83.85 & 75.86 & 79.56 \\ \cline{2-4}  & Negative & 84.41 & 88.34 & 86.33 \\ \cline{2-4}  & Neutral & 74.21 & 73.44 & 73.82 \\ \hline \multirow{2}{*}{Macro average} & 80.82 & 79.15 & 79.90 \\ \cline{2-4}  & Weighted average & 82.35 & 82.38 & 82.29 \\ \hline \multicolumn{4}{c}{Overall accuracy} & 82.38 \\ \hline \hline \end{tabular}
\end{table} 
Table 8: Classification report for the SER algorithm integrated into the NeuroPredict platform. tive diseases, such as AD, PD, or MS, is the main focus of an ongoing four year research project that is currently in its second year of implementation. The NeuroPredict platform integrates health monitoring data from multiple sources: IoMT devices available on the market, in-house-developed devices, and self-reported data using web forms. Based on need, new devices may be integrated into the platform using the data integration module of the platform, with the requirement that the device's manufacturer provide access to the acquired data through an SDK or an API. Additionally, new forms for self-reporting health data may be created using the web interfaces of the platform. The multitude of health data sources that are continuously acquired by the integrated IoMT devices allow for the building of complete representations of the monitored subjects. Using the extensive data collections created for each patient, predictive models may be created and utilized to monitor and predict the progression of the three specific diseases: AD, PD, and MS. The following functionalities have been designed: motor function monitoring; cognitive function monitoring and assessment; sleep monitoring; daily (physical) activity monitoring, emotional state monitoring, speech and language ability evaluation and monitoring, and general health monitoring. These functionalities are designed for tracking and predicting symptoms and conditions related to the three targeted diseases and also for general well-being evaluation and safety assurance for the monitored subject (such as through fall detection and location tracking or by detecting dangerous environmental conditions). The targeted users of the NeuroPredict platform are medical professionals, formal and informal caregivers, and patients. Medical professionals may utilize the platform's components to monitor their patients using patient charts filled with automatically collected data from the IoMT devices or manually input data in forms during checkups or self-reported data in symptoms logs; creating customized treatment and monitoring plans; utilizing the platform's integrated algorithms for assisted diagnosis (the final verdict will always be given by a medical professional); and easily observing abnormal values or trends for health metrics. Formal and informal caregivers may also use the platform to see recommended treatment and monitoring plans for their patients/relatives, to manually input health data, or for more easily supervise the general well-being of their patients/relatives. Patients benefit from improved quality of care services received from medical professionals and caregivers, may use the tools for self-reporting health data and perceived symptoms, and may check their recommended personalized treatment and monitoring plan. The integrated emotion recognition algorithm allows the assessment of the mental states of the monitored patients into one of the three possible emotional states: positive, neutral, or negative. Emotion detection is an essential component of the NeuroPredict platform.