Introduction
Over ten subtypes of disorders associated with pathological tremor have been identified by the medical community [
1] of which Essential Tremor (ET) and Parkinson’s Disease (PD) are considered the most pervasive. Overall pathological tremor prevalence ranges from 2% to well over 10% in the elderly (65 years or older) [
2‐
4]. A large percentage, some estimates are as high as 60%, of those affected by tremor experience disability in their activities of daily living [
5,
6], and more than a quarter struggle to find relief through conventional treatments [
7]. Treatment with pharmacotherapy can be challenging as individual responses vary widely; a typical scenario is that a given medication is partially efficacious at low dosages, but increasing dosage results in a trade-off between efficacy and associated side effects [
8]. When medications are effective, the expected tremor reduction is around 50–60% [
6,
9]. Individuals with a disabling or medication refractory tremor, may have the option for one of several surgical procedures in the form of Deep Brain Stimulation (DBS), lesioning techniques such as γ knife radiosurgery (invasive), and magnetic resonance-guided focused ultrasound (non-invasive) [
9,
10]. In practice, less than 2% of PD patients are targeted for treatment with DBS [
11], with about 40,000 PD and ET patients undergoing DBS worldwide by 2013 [
12]. A small but considerable proportion of individuals undergoing DBS experience side effects or complications. About 70–90% of DBS patients experience reduction of tremor that can range from 60 to 90% [
8,
13]. Focused ultrasound offers a non-invasive thalamotomy procedure that has been demonstrated to reduce tremor [
14]. Risks for surgical procedures include intracerebral hemorrhage and other potential neurologic impairments [
15].
There is, therefore, a persuasive case for alternative therapies for individuals with pathological tremor who respond poorly to medications and DBS or for whom surgery is not an option. Perhaps one of the strongest arguments for robotic devices for treatment of tremor is that such devices could successfully treat tremors arising from different biological etiologies (e.g. resting, postural and kinetic) with possible minor tremor-specific optimizations.
A number of systems designed for the suppression of upper limb tremor employed suppressive technologies such as viscous and magnetic fluids, magnetic particle brakes, pneumatic actuators and DC motors [
16‐
26] while others employed Functional Electrical Stimulation (FES) [
4,
27‐
35]. Of the above systems, several were demonstrated with individuals with tremor [
17‐
20,
27‐
32] resulting in ~ 20–88% tremor attenuation levels, although attenuation levels were not computed consistently across the studies and should therefore be considered cautiously. The remaining systems focused on design or experimental testing whereby the human motion (tremor and voluntary) was simulated physically or in software [
4,
16,
22‐
26,
33‐
35]. Limitations of non FES technologies tend to be related to size and weight whereas the main limitations associated with FES are muscle fatigue, stimulation discomfort and difficulty in accessing specific muscles through surface electrodes. All technologies may require some amount of customized tuning per individual’s physiology, however, potentially more so with FES.
Common tremor suppression methods involve estimating the tremor and applying an opposite canceling signal, for example in the form of velocity or force exerted by an actuator. In the case of FES an out of phase stimulation may be applied to, say, the flexor muscle concurrent with its antagonist tremor burst. Alternatively, some approaches modulate the impedance of the human-machine system [
20,
24,
29]. In the case of FES this may involve stimulation of both flexor and extensor simultaneously in order to increase the stiffness and viscosity of the limb. Another recent approach for FES involves stimulating below the motor threshold to mitigate the issue of fatigue [
4,
28]. The results provide some evidence of residual suppression even after stimulation has stopped, however, with larger variability in performance and lower tremor attenuation.
When mechanically suppressing tremor, there is a risk of preventing the individual with tremor from performing volitional movements. Notably, the potential negative effects on the volitional movement are seldom addressed in the literature. Rocon et al. employed a feedback loop aimed at reducing the forces resisting the voluntary movement [
20], however, with reported results focusing on the tremor motion. A study by Taheri et al. reported the actuator resistive forces to the voluntary motions in a tremor simulation system [
26]. One study involving a single individual exhibiting intention tremor, due to MS, was identified that reported the impact of FES suppression on the voluntary motion in a step-target tracking task [
32]. No other studies with individuals with tremor were identified that quantitively assess the impact on the volitional motion using an engineering solution.
Different from conventional suppression techniques, the orthosis employed in this work tracks the voluntary motion, estimated from a force signal [
36], while the tremor signal is seen as interference to the volitional motion and is consequently rejected by the controller.
The aim of this work is to show viability of the suppression approach, using an elbow orthosis prototype [
37], tested with individuals with pathological tremor. The above aim can be explored as two separate questions. First, is the approach effective in suppressing the involuntary motion, and second, is the interference to the voluntary motion quantifiably limited. The application of the suppression approach with an orthosis can provide an important therapeutic alternative for individuals with tremor, with potential to improve independence and quality of life.
Discussion
This tremor suppression investigation relies on a recently developed suppression approach coupled with a previously tested wearable technology targeting the elbow joint [
37], which has been shown to be central to most activities of daily living [
47,
48]. In evaluating the suppression approach, the effects to both involuntary and voluntary motions are considered. The results indicate better tremor suppression than comparable interventions. Moreover, voluntary motion interference is shown to be limited, statistically speaking, albeit not completely eliminated.
All participants in this study were right-handed. For all participants, other than T01, T07 and T08, the tremor was more severe on the right side and all but one participant (T08) were tested on the more severe side. Due to a medical condition, T08 was tested on the right side (left side was more severe). It is interesting to note that in the literature there is conflicting evidence as to whether the more severe side is likely to be the dominant side [
49], the non-dominant side [
50,
51] or neither [
52].
Two key observations related to the tremor measures that can be appreciated visually in Fig.
2a are that attenuation was overall higher for random relative to sinusoid target movements and for slower relative to faster target movements. A matching subjective observation of the participants was that tracking faster target motions was easier to perform while inducing less tremor. There was a relatively large variation between ET participants mean frequency in Fig.
2b (T01, T04, T05, T06, T08 and T09). Only two of the recruited participants were identified as PD (T02 and T03); therefore, it is difficult to determine if similar frequency variations would be observed among the PD subjects. The typical bandwidth for ET, however, is considered to be wider, overlapping below and above that of PD [
1]. The intrasubject tremor frequency variations in this study are comparable with those in [
53] but smaller than in [
54]. In instances were a clear tremor peak was not detectable (mainly for T08 and T09), the PSD frequency peak search would occasionally result in a frequency near the search lower limit of 3 Hz. The TETRAS score was fairly consistent across study participants as evidenced by the small standard deviation in Table
1. For participant T09 who had substantially milder tremor, which was barely visible, it is interesting to note also a substantially lower tremor reduction of 85%.
Observations related to the voluntary measures are considered next. Random motion tasks were associated with larger power change values and lower tracking errors as can be appreciated from Fig.
3. Slow motions were also associated with lower tracking errors. The above is likely related to the lower speed and the more gradual increase in motion range of the random tasks. Despite the two weaker correlations in Fig.
5 for the TSO, generally, an improvement in one metric suggests improvements of other metrics. Of key interest in this study is the difference in the voluntary performance of the TSO relative to the MO. A velocity controller was utilized in the suppression approach which may explain the paired difference test marginal result for position RMSE but not for velocity RMSE or voluntary power change, which was also based off the velocity signal. Participant T08 demonstrated the largest difference in the voluntary power change metric (49.88%) between the MO and the TSO (Fig.
3a). The large voluntary power change difference may be related to the limited ROM the participant was achieving with the MO compared to the TSO. The difference in ROM could be due to device fitting issues, or alternatively, to the TSO inherent actuation enabling greater ROM (more signal power). Corresponding large differences do not appear in the subject’s position or velocity RMSE’s, in Fig.
3b and c. For participant T08, only two repetitions for the fast random movement were collected. Beyond paired difference tests, it is important to consider the effect sizes for the differences between the TSO and MO were only 0.9 deg. for the position RMSE, 0.02 rad/s for the velocity RMSE and 6.64% for the power change (section
Voluntary motion component). Furthermore, when excluding T08, the power change between MO and TSO increases by only 1.23%. Referring to Fig.
3d, tasks with an overall lower velocity resulted in overall lower interaction torque, as expected from an admittance controlled system.
Potential limitations are recognized, related to the suppression system and approach. Overall, high velocity motions have been shown to have a dominant contribution to degraded voluntary performance. Also, voluntary interaction forces should be further reduced in future work. Some looseness and play between the orthosis and the human arm as well as within the orthosis mechanism exists, potentially resulting in some of the tremor not being detected. Modifications to reduce backlash and play may increase the signal to noise ratio and thus improve the tremor suppression. Follow up explorations should also address limitations to the study design. The study does not evaluate the passive effect of the mass and inertia of the TSO on tremor suppression and on voluntary motion. Thus, in future work the suppression with the TSO in off mode should be demonstrated to assess the mass and inertia contribution. Whether the tremor suppression is primarily caused by the active suppression approach or the passive mass and inertia is, however, deemed less critical so long that the negative impact to the voluntary motion remains limited, as shown in this work. Furthermore, the suppression approach demonstrated significant attenuation using substantially less mass and inertia in previous work [
36]. Another potential protocol limitation involves order effects due to fatigue and training when the TSO is tested after the MO. If these effects exist, they may be mitigated by randomizing the TSO and MO order. Fatigue may have also occurred due to the TSO resistance, particularly at later stages in the testing session, and may have worsened voluntary tracking results. TETRAS was used to score two PD subjects in this study despite being targeted at ET. Additionally, TETRAS scoring may have been influenced by the preceding device testing. Nevertheless, if there was an effect due to the device testing, it may be assumed to be roughly equal for all participants. Since this is an assistive device, the TETRAS outcome is not considered crucial for the device’s performance evaluation. Therefore, in this preliminary study, the implication of post testing assessment as well as PD subjects assessment is not considered critical. The study protocol evaluated tremor during active movement. In future work, rest tremor could be incorporated for evaluation. RMSE position and velocity measures could potentially also be used to assess tremor suppression. In this work, the voluntary component contribution to tracking RMSE was much more substantial relative to the tremor contribution, perhaps due to the large voluntary motion amplitude or due to sensor sensitivity. As a result, comparing the MO to the TSO tracking errors resulted in poor RMSE tremor suppression sensitivity. Subjects were asked to abstain from medications for 12 h before testing, yet this time span may not be enough for ET subjects (taking Primidone or Propranolol) to be in a clinically-defined off state. Although tremor was observable in all study subjects, by motion sensors and by TETRAS, the implication is that tremor could be more severe in fully off-medication individuals. It is expected, however, that an increase in tremor signal would result in better voluntary and tremor decomposition, by the control system, and consequently better voluntary motion tracking and noise (tremor) rejection. In future work, recording of medications may help to guide abstinence times. Patients with PD may exhibit involuntary and burst-like movements, other than tremor, such as dyskinesia, with a frequency spectra overlapping both voluntary and tremor motions. It should be noted, our inclusion criteria did not explicitly identify such movement abnormalities. The suppression approach is designed such that motions residing within the frequency band defined for tremor (2–10 Hz) are considered a disturbance and consequently rejected. Our device and control approach successfully rejected motions in this frequency band during the tests as demonstrated in Figs.
2 and
4 (PSD plots). Non-tremor motor disorder movements that overlap tremor frequencies are therefore suppressed along with the tremor. On the other hand, we expect that our system will not be effective in suppressing involuntary movement in the frequency band 0–2 Hz and that voluntary motions will be affected by such motor disorders. Nevertheless, the effect to the MO and TSO voluntary performance may be roughly the same such that voluntary tracking can still be compared and evaluated.
The MO was used in this study mainly as a performance benchmark for the TSO. Nevertheless, in a real world scenario, per user initialization of the ABPF center frequency would be needed and could still be performed with the MO, as was done in this study. Alternatively, initialization and if needed, update of the tremor center frequency may be realized without the MO by modifying the TSO and the tremor estimation algorithm. A few participants commented they noticed a favourable effect of the suppression on their tremor and some expressed interest in such a device if size and weight were reduced. Other studies reported some migration of tremor to nearby joints [
29]. A similar phenomenon was not observed in this study. It is expected that by adapting the suppression orthosis to other joints (e.g. the wrist), a similar alleviation of tremor would be observed. However, follow-up investigations would be needed to verify this. Additional studies, involving larger populations, are also needed to validate the technology. The ABPF fundamental tremor frequency was the only subject related parameter requiring calibration in the proposed system, reducing the approach sensitivity to different users or neurophysiological changes.