Cloud-Integrated AI Solutions for Personalized Assistive Technologies in Cerebral Palsy

Personalized assistive technologies are crucial for individuals with Cerebral Palsy (CP) to enhance their quality of life since the disorder presents significant obstacles in motor and cognitive skills. This paper looks at how cloud computing and artificial intelligence (AI) may work together to provide personalized solutions for people with CP. Efficiently handling varied datasets and AI models is made possible by the cloud infrastructure's scalability of data processing and storage capabilities. Assistive devices use Artificial Neural Networks (ANNs) to provide real-time feedback and adaptive assistance to decipher sensor data. Utilizing AI algorithms in the cloud enables continuous learning processes, which enables the personalization of assistive technology according to specific needs and ever-changing circumstances. This research highlights the importance of integrating AI solutions into the cloud to improve personalized care for CP patients. The proposed method uses the Mendeley CP Dataset to train the ANN model, allowing precise predictions of assistive device requirements for improving personalized assistive technology solutions for individuals with CP. These technologies may help with mobility, communication, and general independence. CP assistive system, which is based on ANNs and integrated into the cloud, enhanced user interaction efficiency by 45%, and achieved 92% accuracy in gesture detection and 89% in voice prediction.