Closed-Loop Control of the Centre of Pressure in Post-Stroke Patients With Balance Impairments

When a lightly touched surface is moved according to a closed-loop control law, it has been shown in young adults that the centre of pressure (CoP) can be displaced in a controllable way without the conscious cooperation of participants. In this closed-loop paradigm, the surface velocity was continuously adjusted according to the CoP position. Since the closed-loop control of the CoP does not require the participant's voluntary cooperation, it could be of interest for the development of innovative biofeedback devices in balance rehabilitation. Before anticipating the implementation of this closed-loop control paradigm with patients, it is necessary to establish its effects on people suffering from balance impairments. The aim of this paper was to assess the effects of this CoP closed-loop control in post-stroke (PS) patients and aged-matched healthy controls. Efficacy of the closed-loop control for driving the patients' CoP was assessed using the saturation time and two scores computing the error between the predefined and the current CoP trajectories. 68% and 83% of the trials were considered as successful in patients and controls, respectively. The global tracking error of the closed-loop score was similar between the two groups. However, when examining the real CoP displacement from the starting position to the desired one, PS patients responded to the closed-loop control to a lesser extent than controls. These results, obtained in the same conditions for healthy and PS individuals could be improved by tuning the closed-loop parameters according to individual characteristics. This paper paves the road towards the development of involuntary/automatic biofeedback techniques in more ecological conditions.

USING SHORT-TIME FOURIER TRANSFORM AND WAVELET PACKET TRANSFORM TO ATTENUATE NOISE FROM HEART SOUND SIGNAL FOR WEARABLE E-HEALTHCARE DEVICE

A soft-computing method attenuating noise from heart sound (HS) signal for wearable e-healthcare device is proposed. The HS signal is decomposed by third-level wavelet packet transform (WPT). An automatic HS cycle detection algorithm is applied to find HS cycles in the (3, 0) leaf signal of WPT tree. Based on the quasi-cyclic feature of HS, short-time Fourier transform is implemented for cycles of each WPT tree leaf signal to decompose each cycle into time-frequency fragments which are called particles. Furthermore, the novel cuboid method is proposed to identify constituents of HS and noise from such generated particles. The particles representing HS are then retained and merged into noise-quasi-free WPT tree leaf signals. Eventually the inverse WPT (IWPT) is employed to build the noise-quasi-free HS signal. The method is assessed using mean square error (MSE) and compared with wavelet multi-threshold method (WMTM) and Tang's method. The experimental results show that the proposed method not only filters HS signal effectively but also well retains its pathological information.

Closed loop kinesthetic feedback for postural control rehabilitation

Postural control rehabilitation may benefit from the use of smart devices providing biofeedback. This approach consists of increasing the patients perception of their postural state. Namely, postural state is monitored and fed back in real time to the patients through one or more sensory channels. This allows implementing rehabilitation exercises where the patients control their posture with the help of additional sensory inputs. In this paper, a closed loop control of the Center-Of-Pressure (CoP) based on kinesthetic feedback is proposed as a new form of biofeedback. The motion of a one Degree of Freedom (DoF) translational device, lightly touched by the patient's forefinger, is servoed to the patient's CoP position extracted from the measurements of a force plate on which he/she stands. As a result, the patient's CoP can be controllably displaced. A first set of experiments is used to prove the feasibility of this closed-loop control under ideal conditions favoring the perception of the kinesthetic feedback, while the subject is totally unaware of the context. A second set of experiments is then proposed to evaluate the robustness of this approach under experimental conditions that are more realistic with regards to the clinical context of a rehabilitation program involving biofeedback-based exercises.