An adaptive frequency oscillator learning mechanism was
firstly developed by Righetti et al. [55], in order to synchronize
with the instantaneous frequency and phase of any periodic input
signal. This model has been widely used in robotics field, for
example, as a central pattern generator [56]. Ronsse et al. [57]
extend this concept to the wearable robotics researches, with
the aim of capturing periodic locomotion-related signals features
(i.e. phase, frequency, amplitude, offset) in walking or cyclic
rehabilitation exercises. Besides the adaptive frequency oscillators,
there are also some applications of traditional neural oscillators
for their synchronization and inhibition properties [58]. In recent
years, adaptive oscillators-based control is obtaining greater
attention, however, in our literature review, it is found that its
application is limited to subjects who can deliver periodic and
stable locomotion-related signals, and mostly validated on the hip
joint actuation (referring to 4.1.1, hip exoskeleton).