Predicting energy consumption in humans using joint space methods

Humans act as transducers that transform chemical energy from food, water, and air into mechanical work and the thermal energy of heat loss. Although this energy expenditure can be experimentally measured, methods of predicting energy expenditure have not been broadly studied. This work introduces a new formulation of metabolic energy consumption based on muscle physiology and the equations of motion for the human body. Kinematic and kinetic data from a gait experiment and an over-Arm throwing simulation are used to illustrate and validate this new model. The results extend the capabilities of dynamic human modeling to include metabolic energy prediction in general tasks. This novel formulation is useful for the investigation of human performance with applications in physical therapy, rehabilitation, and sports.