The Resonating Arm Exerciser: design and pilot testing of a mechanically passive rehabilitation device that mimics robotic active assistance

Abstract

Background: Robotic arm therapy devices that incorporate actuated assistance can enhance arm recovery, motivate patients to practice, and allow therapists to deliver semi-autonomous training. However, because such devices are often complex and actively apply forces, they have not achieved widespread use in rehabilitation clinics or at home. This paper describes the design and pilot testing of a simple, mechanically passive device that provides robot-like assistance for active arm training using the principle of mechanical resonance.

Methods: The Resonating Arm Exerciser (RAE) consists of a lever that attaches to the push rim of a wheelchair, a forearm support, and an elastic band that stores energy. Patients push and pull on the lever to roll the wheelchair back and forth by about 20 cm around a neutral position. We performed two separate pilot studies of the device. In the first, we tested whether the predicted resonant properties of RAE amplified a user's arm mobility by comparing his or her active range of motion (AROM) in the device achieved during a single, sustained push and pull to the AROM achieved during rocking. In a second pilot study designed to test the therapeutic potential of the device, eight participants with chronic stroke (35 ± 24 months since injury) and a mean, stable, initial upper extremity Fugl-Meyer (FM) score of 17 ± 8 / 66 exercised with RAE for eight 45 minute sessions over three weeks. The primary outcome measure was the average AROM measured with a tilt sensor during a one minute test, and the secondary outcome measures were the FM score and the visual analog scale for arm pain.

Results: In the first pilot study, we found people with a severe motor impairment after stroke intuitively found the resonant frequency of the chair, and the mechanical resonance of RAE amplified their arm AROM by a factor of about 2. In the second pilot study, AROM increased by 66% ± 20% (p = 0.003). The mean FM score increase was 8.5 ± 4 pts (p = 0.009). Subjects did not report discomfort or an increase in arm pain with rocking. Improvements were sustained at three months.

Conclusions: These results demonstrate that a simple mechanical device that snaps onto a manual wheelchair can use resonance to assist arm training, and that such training shows potential for safely increasing arm movement ability for people with severe chronic hemiparetic stroke.

Figures

Figure 1

Left: A schematic drawing of RAE detailing the movement of the various components during operation (the elastic bands that support the arm trough are excluded for clarity, but can be seen in the photo to the right). The participant uses RAE by pushing rhythmically on the lever in the parasagittal plane, rolling the wheelchair about 20 cm back and forth on the floor at its resonant frequency. The front wheels are rigidly fixed parallel to the rear wheels, so the wheelchair does not rotate in and out of the plane of the figure during operation. Right: A participant’s right arm placed with a “flat-palm” grip in RAE. The elastic bands supporting the arm trough can be seen on both sides of the hand.

Figure 2

The step response of a subject in RAE. The superimposed dotted line shows the theoretical angle an accelerometer would measure during the step response of a second order system parameterized with the experimentally identified damping ratio and natural frequency.

Figure 3

The arm AROM of individuals with chronic stroke in RAE. The “without rocking” bar shows the AROM achieved with RAE with a single effort, defined as the difference between a single, sustained maximum push, and a single, sustained maximum pull. The “with rocking” bar shows AROM when participants were asked to rock at whatever frequency felt natural. The amplitude of movement was 1.7 times larger when participants were rocking, a significant difference (p = 0.041).

Figure 4

Left: A plot of the mean AROM for 6 participants (the remaining two participants had full range of motion along the device at study start). Error bars show +/− 1 SD. Each participant had one baseline measurement and 8 measurements during the exercise period. The solid line is the linear regression showing a positive slope of 2.0 degrees per session (R^2 = 0.80, p = .003). Right: The mean FM scores for the Exercise-Rest (n = 3) and Rest-Exercise (n = 5) groups. Error bars show +/−1 SD. Significant changes are marked with a ‘*’.

Figure 5

The median FM scores (n = 6) from before therapy, immediately after therapy, and at a three month follow up assessment. A significant change in FM score was detected before and after therapy (p = 0.042), but no significant change was detected three months later (p = 0.80), although there was a slight downward trend. Error bars show the interquartile range.

Figure 6

The results of the pain measurements, showing the average perceived levels of pain before a session, after that session, and before the following session. The dashed lines represent each individual participant and the solid line represents the mean values for all 8 participants.

Figure 7

Above: Comparison of the FM and AROM assessments for 6 participants (the remaining two participants had full AROM along the device at study start). The solid line represents the regression line for the AROM data, while the dashed line shows the change in FM score before and after training. Below: Comparison of the slope of the AROM data vs. the change in FM score for 6 participants (the remaining two participants had full range of motion along RAE at study start). The dashed line is an estimate of a linear relationship between the two measurements (R = 0.75, p = 0.09).

Figure 8

Theoretical energy cost of rocking in RAE. The energy cost for each rocking frequency was computed using a mathematical model of human energy expenditure [25] for a human driving a second-order underdamped system with the same damping ratio and natural frequency identified in Figure 2 above. Using this model, we calculated the instantaneous rate of energy expenditure as the sum of the velocity and force dependent heat losses in the muscle and the rate of mechanical work being done, then integrated this rate over a one minute time span to calculate total energy expenditure.