K Waring

A novel method of using accelerometry for upper limb FES control

This paper reports on a novel approach to using a 3-axis accelerometer to capture body segment angle for upper limb functional electrical stimulation (FES) control. The approach calculates the angle between the accelerometer x-axis and the gravity vector, while avoiding poor sensitivity at certain angles and minimizing errors when true acceleration is relatively large in comparison to gravity. This approach was incorporated into a state-machine controller which is used for the real-time control of FES during upper limb functional task performance. An experimental approach was used to validate the new method. Two participants with different upper limb impairments resulting from a stroke carried out four different FES-assisted tasks. Comparisons were made between angle calculated from arm-mounted accelerometer data using our algorithm and angle calculated from limb-mounted reflective marker data. After removal of coordinate misalignment error, mean error across tasks and subjects ranged between 1.4 and 2.9°. The approach shows promise for use in the control of upper limb FES and other human movement applications where true acceleration is relatively small in comparison with gravity.

Prediction of setup times for an advanced upper limb functional electrical stimulation system

Introduction Rehabilitation devices take time to don, and longer or unpredictable setup time impacts on usage. This paper reports on the development of a model to predict setup time for upper limb functional electrical stimulation. Methods Participants’ level of impairment (Fugl Meyer-Upper Extremity Scale), function (Action Research Arm Test) and mental status (Mini Mental Scale) were measured. Setup times for each stage of the setup process and total setup times were recorded. A predictive model of setup time was devised using upper limb impairment and task complexity. Results Six participants with stroke were recruited, mean age 60 (±17) years and mean time since stroke 9.8 (±9.6) years. Mean Fugl Meyer-Upper Extremity score was 31.1 (±6), Action Research Arm Test 10.4 (±7.9) and Mini Mental Scale 26.1 (±2.7). Linear regression analysis showed that upper limb impairment and task complexity most effectively predicted setup time (51% as compared with 39%) (F(2,21) = 12.782, adjusted R2 = 0.506; p < .05). Conclusions A model to predict setup time based on upper limb impairment and task complexity accounted for 51% of the variation in setup time. Further studies are required to test the model in real-world settings and to identify other contributing factors.

FES-UPP: A Flexible Functional Electrical Stimulation System to Support Upper Limb Functional Activity Practice

There is good evidence supporting highly intensive, repetitive, activity-focused, voluntary-initiated practice as a key to driving recovery of upper limb function following stroke. Functional electrical stimulation (FES) offers a potential mechanism to efficiently deliver this type of therapy, but current commercial devices are too inflexible and/or insufficiently automated, in some cases requiring engineering support. In this paper, we report a new, flexible upper limb FES system, FES-UPP, which addresses the issues above. The FES-UPP system consists of a 5-channel stimulator running a flexible FES finite state machine (FSM) controller, the associated setup software that guides therapists through the setup of FSM controllers via five setup stages, and finally the Session Manager used to guide the patient in repeated attempts at the activities(s) and provide feedback on their performance. The FSM controller represents a functional activity as a sequence of movement phases. The output for each phase implements the stimulations to one or more muscles. Progression between movement phases is governed by user-defined rules. As part of a clinical investigation of the system, nine therapists used the FES-UPP system to set up FES-supported activities with twenty two patient participants with impaired upper-limbs. Therapists with little or no FES experience and without any programming skills could use the system in their usual clinical settings, without engineering support. Different functional activities, tailored to suit the upper limb impairment levels of each participant were used, in up to 8 sessions of FES-supported therapy per participant. The efficiency of delivery of the therapy using FES-UPP was promising when compared with published data on traditional face-face therapy. The FES-UPP system described in this paper has been shown to allow therapists with little or no FES experience and without any programming skills to set up state-machine FES controllers bespoke to the patient’s impairment patterns and activity requirements, without engineering support. The clinical results demonstrated that the system can be used to efficiently deliver high intensity, activity-focused therapy. Nevertheless, further work to reduce setup time is still required.