Enhancing healthcare IoT systems for diabetic patient monitoring: Integration of Harris Hawks and grasshopper optimization algorithms.

The integration of the Internet of Things (IoT) in healthcare, especially for people with diabetes, allows for constant health monitoring. This means that doctors can watch over patients' health more closely, making sure they catch any issues early on. With this technology, healthcare workers can be more accurate and effective when keeping an eye on how patients are doing. This not only helps in keeping track of patients' health in real-time but also makes the whole process more reliable and efficient.By implementing appropriate routing techniques, the transmission of diabetic patients' data to medical centers will facilitate real-time and timely responses from healthcare professionals. The grasshopper optimization algorithm is employed in the proposed approach to cluster network nodes, resulting in the formation of a network tree that facilitates the establishment of connections between the cluster head and the base station. After identifying the cluster head and establishing the clusters, the second stage of routing is implemented by employing the Harris Hawks optimization algorithm. This algorithm ensures that the data pertaining to diabetic patients is transmitted to the treatment centers and hospitals with minimal delay. For node routing, the optimal next step is selected based on the parameters such as the residual energy of the node, the ratio of delivered data packages, and the number of the neighbors of the node. To continue, first, the MATLAB software is utilized to simulate the proposed method, and then, it is compared with other similar methods. This comparison is conducted based on various parameters, including delay, energy consumption, network throughput, and network lifespan. Compared to other methods, the proposed method demonstrates a significant 33% improvement in the average point-to-point delay parameter in the subsequent iterations or rounds.

The effect of emotion regulation training on family relationships of hyperactive children.

INTRODUCTION: One of the psychiatric disorders related to childhood is attention deficit hyperactivity disorder that can negatively affect the family interactions of these children. Parents of these children, especially the mother as the main caregiver, need comprehensive training to make a positive difference in their attitudes and behaviors with these children. The purpose of this study was to investigate the effect of emotion regulation training on family relationships in hyperactive children. METHODS: This was a randomized clinical trial study with a control group performed on eighty mothers of hyperactive children who were selected randomly. The intervention group members attended emotion regulation skills training sessions for one session of 90 min each week for 8 weeks. During the training course in the intervention group, the control group did not receive any training. Data collection tools included demographic information questionnaires, Mother-Child Relationship Evaluation, and Rahim Organizational Conflict Inventory-II. Data analysis was performed by descriptive statistics and the analysis of covariance. RESULTS: The mean scores of the mother-child relationship in the intervention group showed a significant improvement in the subscales of acceptance, overprotection, facilitation, and rejection (P < 0.0001). The results of this research also showed improvements in all the five communication styles of integrating, avoiding, compromising, obliging (P < 0.0001), and dominating (P < 0.012) between spouses. CONCLUSION: It seems that the emotion regulation training approach in mothers with hyperactive children improved both the mother-child relationship and the interactive spousal styles and can be considered by the managers of treatment and rehabilitation field as an adjunctive therapy for the families of these children.