## 3 Perspectives and Outcomes of the Presented RHMS with a Focus on Diet-Related Approaches
### Schizophrenia, Dietary Habits, and Physical Health
#### 3.2.2 RHMS Role (NeuroPredict Platform) in Managing Schizophrenia
This empowers individuals with information to make informed decisions about their dietary habits;
* _Dietary adherence and symptom correlation_: Correlations between dietary adherence and symptomatology can be explored through the NeuroPredict Platform. Understanding how dietary choices may relate to the severity of symptoms provides valuable information for both individuals and healthcare providers, helping in the management of this disease;
* _Medication adherence monitoring_: The NeuroPredict Platform can diligently track medication adherence through reminders and notifications. By analysing patterns of medication adherence, healthcare providers gain a comprehensive understanding of the treatment plan's effectiveness, enabling necessary adjustments as needed;* _Sleep patterns and quality monitoring_: The monitoring of sleep patterns becomes instrumental in identifying disruptions, a common occurrence in individuals with schizophrenia, enhancing sleep hygiene;
* _Activity and movement tracking_: Harness NeuroPredict Platform capabilities to monitor daily activities and movement patterns. Changes in activity levels provide valuable insights into the individual's overall well-being and mental state, aiding in a holistic approach to schizophrenia management;
* _Stress level monitoring_: Some NeuroPredict Platform devices feature stress tracking capabilities. The continuous monitoring of stress levels assists healthcare providers in understanding triggers and developing targeted strategies for stress management, a particularly relevant aspect of schizophrenia care;
* _Social interaction assessment_: The NeuroPredict Platform data offer insights into social interactions through communication patterns, interaction frequency, and engagement with social activities. Changes in social behaviour can serve as indicators of the individual's mental health, enriching the assessment process;
* _Physiological measurements_: Integrate physiological measurements, such as HRV and skin conductance, into the NeuroPredict Platform. These metrics provide additional information about the individual's autonomic nervous system and stress response, contributing to a more comprehensive health profile;
* _Environmental triggers analysis_: The NeuroPredict Platform may include sensors to detect environmental factors like noise levels and ambient light. Analysing these data points helps identify potential environmental triggers impacting mental health, contributing to a more holistic understanding of schizophrenia triggers;
* _Mood and symptom tracking_: Incorporating features allowing individuals to log their moods, symptoms, or perceived stress levels directly into the NeuroPredict Platform. This self-reported data complement objective measurements, contributing to a more nuanced understanding of the individual's mental health. Being a neuropsychiatric syndrome, schizophrenia exhibits a range of symptoms encompassing psychotic features like delusions and hallucinations, negative aspects such as diminished motivation and blunted affect, and cognitive difficulties including attention deficits, working memory issues, verbal fluency challenges, and various problems in social cognition. Acknowledging the imperative for improved management, there is a growing recognition of the significance of continuous remote monitoring through the help of RHMS solutions, such as the NeuroPredict Platform. This involves identifying both subjective and objective markers to detect signs of psychotic relapse, aiming for more effective control over conditions within the schizophrenia spectrum. 2.3 Potential of the NeuroPredict Platform's Capabilities for Schizophrenia Management: ML for Personalized Interventions  
ML for predictive analytics in the context of schizophrenia involves utilising advanced algorithms to analyse data from the NeuroPredict Platform over an extended period. This approach is particularly valuable, as it aims to identify patterns and trends that may precede relapses or symptom exacerbations in individuals with schizophrenia.