## 1 Introduction  
Stroke is presently one of the most prevalent cardiovascular diseases. According to the World Health Organization, it is estimated that 15 million people worldwide suffer a stroke annually, 10 million of whom survive with disabilities [1]. Treatment, rehabilitation, and caregiving of the stroke survivors could lead to a large financial and societal burden [2]. One critical tool to address this issue is efficient rehabilitation programs to improve recovery speed, such as the introduction of robotic gait assistance programs to help stroke survivors regain their gait abilities [3]. Hemplegia that leads to paralysis of the affected side is a common sequela for stroke survivors [4]. For a normal human gait, dorsiflexion in the swing phase contributes to limb shortening, which is important to ensure toe clearance from the ground [5, 6]. For a stroke hemiplegic patient, however, his or her ankle forces or movement controls may be too weak to perform sufficient dorsiflexion and drop foot could result [7]. This toe-down posture decreases toe clearance and could lead to stumbling or toe dragging while walking [8]. To increase minimum toe clearance (MTC) in the swing phase, stroke survivors tend to perform compensatory movements such as circumduction and hip hiking [9; 10]. However, such compensatory movements during gait rehabilitation could affect optimal gait learning. Robotic ankle-foot orthoses (RAFOs) have been developed in recent decades to support ankle movements during gait rehabilitation, including dorsiflexion assistance in the swing phase [11; 12]. Some studies have indicated that their RAFOs' intervention effects not only improve ankle dorsiflexion angle and foot clearance but also suppress compensatory movements [12; 13]. There are also off-the-shelf RAFO systems, such as RE-Gait\({}^{\text{\textregistered}}\), currently used in robotic gait assistance programs in medical facilities [14]. Although promising intervention results were reported in the available literature, there are still challenges left for RAFO technology, such as the implementation of an assist-as-needed (AAN) control strategy. Robotic systems such as Lokomat and ALEX apply impedance control to enhance voluntary lower-limb movements during gait rehabilitation [15; 16; 17]. It is also commonly held that increasing challenge and voluntary effort during a rehabilitation program accelerates recovery for stroke survivors [15; 18]. Current RAFOs mostly apply positional control, force control, or event-trigger control for ankle movement assistance [19]. Such control strategies purposefully introduce difficulty in movement to further induce a patient's voluntary effort during rehabilitation. Anklebot applies impedance control to provide suitable assistance for ankle movement control [20]. However, most applications are conducted in a sitting posture with the heel on the ground. The AAN control for ankle movement while walking is required, and realization of an AAN strategy on swing-phase dorsiflexion is one of our ultimate goals. Another gap is a systematic gait analysis to verify the RAFO's assistance effects. Current gait measurement instruments can already carry out a systematic gait analysis. An example is an easy gait analysis system that could analyze spatiotemporal gait parameters with Kinect [21]. For lower-limb exoskeletons, a study has assessed not only Lokomat's intervention effect on lower-limb kinematics but also lower-limb range of motion and stiffness which are also important to track a stroke survivor's recovery status [22]. For RAFO research, Anklebot could analyze ankle stiffness [23]. However, to our understanding, very few or no studies have reported systematic gait analysis with an RAFO's assistance. On the other hand, studies on conventional ankle-foot orthoses have reported intervention effects on not only ankle kinematics but also previously mentioned parameters such as MTC and circumduction [24]. Assistance with ankle movements could affect overall gait patterns, and kinematics in individuals should be different.