## 3 Methods
### The NeuroPredict Platform
#### 3.1.4 Medical Monitoring and Evaluation Functionalities in the NeuroPredict Platform
These motor symptoms may be tracked in a monitored environment using IoMT devices. Low-amplitude abnormal body movements like tremor and different types of small movement impairments may be detected and tracked using wearable devices that include accelerometers and gyroscopes and fine-tuned algorithms for detecting the specific movements. Fall detection is also needed when monitoring patients, considering that most of the PD and AD patients are elderly and that PD is closely related to motor function \begin{table}
\begin{tabular}{c c c} \hline \hline
**Category** & **Functionality** & **Modality/** \\  & & **Available Devices** \\ \hline Emotional state monitoring & Voice processing & Microphone/ \\  & & Integrated into a smartphone or a laptop \\ \cline{2-3}  & Physical parameters monitoring for & Multimodal assessment: Heart rate, electrodermal \\  & emotional state identification & Oura Smart Ring, Gitbitt Charge 5, Withings ECG Move, \\  & & Muse EEG headband \\ \cline{2-3}  & Emotional state logs & User reported emotional state through predefined input \\  & & form in the platform \\ \hline Speech and language abilities & Voice processing for language changes & Microphone/ \\  & & Integrated into a smartphone or a laptop \\ \cline{2-3}  & Voice processing for speech clarity & Microphone/ \\  & & Integrated into a smartphone or a laptop \\ \cline{2-3}  & Voice processing for speech changes & Microphone/ \\  & & Integrated into a smartphone or a laptop \\ \hline General health monitoring & Heart monitoring & \\ \cline{2-3}  & Respiratory function evaluation & Spirometer, pulse plethysmography (PPG)/ \\  & & Fitbit Charge 5 \\ \cline{2-3}  & Muscle function assessment & Electromyography (EMG)/ \\  & & MySignals EMG \\ \hline  & & UV-VIS spectroscopy/ \\  & & Integrated into the Medical BlackBox \\ \hline  & & User reported issues through predefined input forms in \\  & & the platform \\ \hline \hline \end{tabular}
\end{table} 
Table 3: _Cont._impairments. The in-house-developed gaitband wearable device continuously records the accelerometer and gyroscope data and sends it to a local processing node for further processing. This is where the AI-based algorithms for fall detection, abnormal movements, and gait and posture analysis are to be implemented and/or further improved. The platform is able to record and identify different movements while the patient is lying in bed by integrating data from the Withings Sleep Analyzer and correlating it with data from other wearable devices that also assess sleep quality. The polysomnography function included in the platform is presented in the following paragraph:  
* Sleep monitoring  
Getting enough quality sleep is essential for both physical and mental health, depression, anxiety, and rumination [13; 78; 79]. When SD is detected and assessed, customized intervention strategies may be defined, including meditation and relaxation techniques and possibly medication for improved sleep. Intuitively, improving sleep quality positively impacts mental and physical health [79]. SD identification may also aid in tracking disease progression. The NeuroPredict platform assesses sleep quality in two ways: (a) through polysomnography and (b) using standardized forms for sleep disorders. NeuroPredict integrates data from the Withings Sleep Analyzer for obtaining polysomnography data. Polysomnography is used to monitor multiple parameters related to sleep. It used to be performed only in clinical or laboratory conditions, but thanks to the advances in IoMT and wearables, necessary devices are widely available at affordable prices. The Withings Sleep Analyzer has been tested against data obtained by polysomnography analysis, the gold standard for sleep diagnostics [72].