Foot placement in balance recovery: complex humans vs simple model

Maintaining balance in daily life is very common to us. For a healthy individual, a fall is simply not supposed to happen. Unfortunately, various conditions such as stroke, spinal cord injury, or aging can lead to balance problems and affect a person's mobility. Robotic devices such as powered orthoses, often referred to as exoskeletons, might provide an outcome for these balance problems. In case of a lower-extremity exoskeleton, the user wears a construction around the legs that should provide support during standing and walking. This support can be to various purposes, such as to reduce the energetic costs of walking, to assist in gait rehabilitation, or to fully take over the walking motion. Although the purpose of the device might differ, most lower-extremity exoskeletons have one thing in common: they have no sense of balance. The exoskeleton cannot react to unexpected disturbances. Because of that, the user has to take the lead in making a balance recovery. This is especially troublesome when the user has balance impairments. To tackle these issues, the control of exoskeletons needs to be improved. Specifically, if the device can assist in balance control in a way that feels natural and intuitive to the user, the device is less likely to conflict with the user's intention. To realize such human-like balance controllers, we must first understand what human balance is, and investigate the way healthy humans regain their balance when it is lost. This might be investigated by applying perturbations to experimental subjects. Disturbances will lead to a balance recovery response involving various balance strategies, such as adjustments in foot placement, or modulation of ankle and hip moments. The focus of this thesis is on human balance recovery in response to external perturbations during walking. Because we mainly deal with walking, foot placement adjustments are expected to be a major, crucial strategy in balance control. This strategy might be replicated using simple inverted pendulum models of walking, which could provide a basis for predicting human-like responses