Abstract
Compared to traditional lower-limb prostheses (LLPs), intelligent LLPs are more versatile devices with emerging technologies, such as microcontrollers and user-controlled interfaces (UCIs). As emerging technologies allow a higher level of automation and more involvement from wearers in the LLP setting adjustments, the previous framework established to study human factors elements that affect wearer-LLP interaction may not be sufficient to understand the new elements (e.g., transparency) and dynamics in this interaction. In addition, the increased complexity of interaction amplifies the limitations of the traditional evaluation approaches of wearer-LLP interaction. Therefore, to ensure wearer acceptance and adoption, from a human factors perspective, we propose a new framework to introduce elements and usability requirements for the wearer-LLP interaction. This paper organizes human factors elements that appear with the development of intelligent LLP technologies into three aspects: wearer, device, and task by using a classic model of the human-machine systems. By adopting Nielsen's five usability requirements, we introduce learnability, efficiency, memorability, use error, and satisfaction into the evaluation of wearer-LLP interaction. We identify two types of wearer-LLP interaction. The first type, direct interaction, occurs when the wearer continuously interacts with the intelligent LLP (primarily when the LLP is in action); the second type, indirect interaction, occurs when the wearer initiates communication with the LLP usually through a UCI to address the current or foreseeable challenges. For each type of interaction, we highlight new elements, such as device transparency and prior knowledge of the wearer with the UCI. In addition, we redefine the usability goals of two types of wearer-LLP interaction with Nelson's five usability requirements and review methods to evaluate the interaction. Researchers and designers for intelligent LLPs should consider the new device elements that may additionally influence wearers' acceptance and the need to interpret findings within the constraints of the specific wearer and task characteristics. The proposed framework can also be used to organize literature and identify gaps for future directions. By adopting the holistic usability requirements, findings across empirical studies can be more comparable. At the end of this paper, we discuss research trends and future directions in the human factors design of intelligent LLPs.