Wireless body area networks (WBANs) are not only an extension and branch of wireless sensor networks (WSNs) but also a practical application area of Internet of Things (IoT). With the extensive development of IoT technology, WBAN can monitor human physiological parameters in real time. Reliable information transmission is an important factor limiting the development of WBAN owing to special path loss and shadowing effect. Therefore, maximizing throughput is a pivotal part of improving system performance. In this paper, a multipoint WBAN (MP-WBAN) with energy harvesting for normal and abnormal scenarios is studied. We propose two different protocols, including a time switching (TS) strategy and a hybrid TS and power splitting (PS) strategy, respectively. In the abnormal scenarios, the access point (AP) harvests independent command signals from sensor nodes in the uplink (UL) and broadcasts dedicated energy signals to all sensor nodes in the downlink (DL). At the same time, the AP simultaneously broadcasts wireless command and energy signals to all sensor nodes in the normal situation. After all sensors harvest energy from the radio frequency (RF) signals, physiological datas can be transfered to the AP in a specific time sequence. We optimize TS ratios to achieve the abnormal situation sum-throughput maximization by utilizing convex optimization techniques. For sum-throughput maximization in normal situation, a near-optimal solution can be acquired by iteratively updating TS ratios and PS ratios. Numerical simulation results show the system performances of sum-throughput can be significantly improved by the proposed algorithms.