  In previous work, the authors proposed a data-driven optimisation algorithm
for the personalisation of human-prosthetic interfaces, demonstrating the
possibility of adapting prosthesis behaviour to its user while the user
performs tasks with it. This method requires that the human and the prosthesis
personalisation algorithm have same pre-defined objective function. This was
previously ensured by providing the human with explicit feedback on what the
objective function is. However, constantly displaying this information to the
prosthesis user is impractical. Moreover, the method utilised task information
in the objective function which may not be available from the wearable sensors
typically used in prosthetic applications. In this work, the previous approach
is extended to use a prosthesis objective function based on implicit human
motor behaviour, which represents able-bodied human motor control and is
measureable using wearable sensors. The approach is tested in a hardware
implementation of the personalisation algorithm on a prosthetic elbow, where
the prosthetic objective function is a function of upper-body compensation, and
is measured using wearable IMUs. Experimental results on able-bodied subjects
using a supernumerary prosthetic elbow mounted on an elbow orthosis suggest
that it is possible to use a prosthesis objective function which is implicit in
human behaviour to achieve collaboration without providing explicit feedback to
the human, motivating further studies.
