Wireless body sensor network (WBSN) allows remote monitoring for different types of applications in security, healthcare and medical domains. Medical applications involve monitoring a large number of patients in real-time environments. The WBSNs in such environments have to be efficient and reliable in terms of data transfer rate, accuracy, latency, and power consumption. This work focuses on studying the slotted access protocol variables in the Contention Access Period (CAP) with the acknowledged uplink traffic (nodes-to-coordinator) under the WBSN channel. This paper proposes a Markov Chain model in WBSN (MC-WBSN) for improving the efficiency and reliability of patients’ remote monitoring systems. The application of the model includes propagating human arm sensory data and analyzing the latency, power consumption, throughput, and higher path loss channel of the WBSN. The results show that the hidden nodes have a great impact on WBSNs performance and throughput. This issue is highly associated with the capacity of the transmitted power.