This study presents the integration of human physiological parameter and robot energy in the trajectory planning to maintain safety and efficiency in human-robot cooperation (HRC). The focus application is a co-lifting and handling of an object using a cooperation of an articulated universal robot (UR5) and human. In the study, actual robot data (joint positions, joint torques, and endeffector forces, etc.) are collected from the robot's internal sensors during HRC through socket communication and python programs. The surface electromyographic (sEMG) signals are collected from the human's upper arms. We verify the change in robot torque with respect to the change in the human muscle activity and propose an optimization cost function that uses the theoretical joint torques for a trajectory and torque due to force interaction. The output of the optimization routine gives a trajectory that is energy efficient as well as demands lower human effort to perform the co-manipulation task.