This review by Tucker et al. provides a comprehensive overview of the state-of-the-art control strategies for portable active lower limb prosthetic and orthotic (P/O) devices, focusing on their application in activities of daily living (ADLs). The authors highlight the importance of integrating these devices with the user's sensory-motor control system to achieve seamless interaction. They propose a generalized control framework that accounts for the physical and informational interactions between the controller, user, environment, and device. This framework is designed to facilitate the development of intelligent and multifunctional controllers for P/O devices, emphasizing the need to consider safety mechanisms at all levels of the control architecture. The review discusses various control strategies, including intention recognition, activity mode recognition, volitional control, and shared control, and provides a classification scheme to compare different approaches. It also explores sensor modalities for motion intention estimation, such as supraspinal neural activity, peripheral neural activity, joint torques and positions, and alternative input methods. Additionally, the paper addresses the use of artificial sensory feedback and substitution to enhance the user's interaction with the device. Environmental interaction is another key aspect, with the authors discussing how the environment can influence the stability, balance, and energy consumption of the device and the user. They suggest that explicit environmental sensing and adaptation will become increasingly important as P/O devices move from controlled environments to real-world settings. Overall, the review underscores the challenges and opportunities in developing controllers for P/O devices that can seamlessly integrate with the user's neuromusculoskeletal system and are practical for use in ADLs. The authors aim to provide guidelines for future research and development, particularly in the context of active physical P/O assistance with locomotive ADLs.This review by Tucker et al. provides a comprehensive overview of the state-of-the-art control strategies for portable active lower limb prosthetic and orthotic (P/O) devices, focusing on their application in activities of daily living (ADLs). The authors highlight the importance of integrating these devices with the user's sensory-motor control system to achieve seamless interaction. They propose a generalized control framework that accounts for the physical and informational interactions between the controller, user, environment, and device. This framework is designed to facilitate the development of intelligent and multifunctional controllers for P/O devices, emphasizing the need to consider safety mechanisms at all levels of the control architecture. The review discusses various control strategies, including intention recognition, activity mode recognition, volitional control, and shared control, and provides a classification scheme to compare different approaches. It also explores sensor modalities for motion intention estimation, such as supraspinal neural activity, peripheral neural activity, joint torques and positions, and alternative input methods. Additionally, the paper addresses the use of artificial sensory feedback and substitution to enhance the user's interaction with the device. Environmental interaction is another key aspect, with the authors discussing how the environment can influence the stability, balance, and energy consumption of the device and the user. They suggest that explicit environmental sensing and adaptation will become increasingly important as P/O devices move from controlled environments to real-world settings. Overall, the review underscores the challenges and opportunities in developing controllers for P/O devices that can seamlessly integrate with the user's neuromusculoskeletal system and are practical for use in ADLs. The authors aim to provide guidelines for future research and development, particularly in the context of active physical P/O assistance with locomotive ADLs.