Abstract: In the age of universal computing, human life is becoming smarterowing to the recent developments in the Internet of Medical Things (IoMT),wearable sensors, and telecommunication innovations, which provide moreeffective and smarter healthcare facilities. IoMT has the potential to shape thefuture of clinical research in the healthcare sector.Wearable sensors, patients,healthcare providers, and caregivers can connect through an IoMT networkusing software, information, and communication technology. Ambientassisted living (AAL) allows the incorporation of emerging innovations intothe routine life events of patients. Machine learning (ML) teaches machinesto learn from human experiences and to use computer algorithms to “learn”information directly instead of relying on a model. As the sample size accessiblefor learning increases, the performance of the algorithms improves.This paper proposes a novel IoMT-enabled smart healthcare framework forAAL to monitor the physical actions of patients using a convolutional neuralnetwork (CNN) algorithm for fast analysis, improved decision-making, andenhanced treatment support. The simulation results showed that the predictionaccuracy of the proposed framework is higher than those of previouslypublished approaches.Keywords: Smart healthcare system; neural network; machine learning