Flood, M.W., O’Callaghan, B.P.F., Diamond P., Liegey J., Hughes G., Lowery M.M. (2020), “Quantitative Clinical Assessment of Motor Function During and Following LSVT-BIG® Therapy”, Journal of NeuroEngineering and Rehabilitation, Jul 13;17(1):92. DOI: 10.1186/s12984-020-00729-8
What is it about?
Many of the clinical tests currently used to assess the motor symptoms of Parkinson’s Disease (PD) evaluate motor function using simple ordinal scores. While informative of general motor function, such scores often fail to characterize specific aspects of movement or subtle changes in performance and are vulnerable to inter-rater variability. Therefore, using these tests to evaluate patient performance in response to physical therapy is not ideal, to which a more objective and quantitative solution is needed. In light of this, recent research has sought to instrument standard clinical tests with wearable sensors to derive quantitative metrics that detail various aspects of motor function, such as gait speed or degree of postural sway. While several studies have previously investigated the effect of LSVT BIG on motor and non-motor symptoms in PD, no study has yet quantitatively evaluated motor function using wearable sensors at multiple stages before, throughout, and up to 13 weeks follow-up. Furthermore, no study of LSVT BIG has examined balance, postural control, and fine motor function using the instrumented sit-to-stand (iSTS), quiet stance (QS), and finger tapping (FT) tasks.
The aim of this study was to instrument standard clinical tests with small wearable accelerometers in order to quantify changes in gait, balance, and fine motor control in individuals with PD undergoing LSVT BIG therapy. Outcome measures from all tasks were compared between those receiving LSVT BIG, non-exercising PD controls, and healthy age-matched controls.
Why is it important?
Data recorded from wearable sensors (e.g. acceleration signals) during instrumented clinical tests can be analyzed in ways that deconstruct complex patterns of movement to identify subtle improvements in motor function. Despite providing clinicians with detailed, quantitative, and objective measures of movement, there has been a dearth of studies employing wearable sensors to monitor patient progression with physical therapy, and in particular LSVT BIG. This study is important as it demonstrates the feasibility of incorporating body-worn accelerometers to objectively monitor and assess adaptions in motor function in individuals with PD following large-amplitude exercise therapy. The results of this study also illustrate the features of gait and balance that are most improved by LSVT BIG and highlights the potential use of wearable sensors to remotely monitor and assess patient mobility outside the clinical environment.
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Perspectives
For additional perspectives on this treatment study and line of treatment research, we asked the lead researcher and author on this study Paul Diamond, OT, a few questions.
Why did you want to study motor function during and after LSVT BIG using wearable sensors?
Despite the various benefits of LSVT BIG described in the literature, issues have been reported about the heterogeneity of clinical scores, potentially reflecting the subjectivity or inconsistency of tests used to assess motor function. We wanted to show that body-worn sensors can provide a solution to this issue by quantifying features of motor function objectively. Furthermore, we wanted to develop new approaches to assessing mobility and fine motor control using accelerometers and to examine how LSVT BIG influences them.
What were the key take away points from this study?
This study demonstrates the potential for wearable sensors to objectively quantify changes in motor function in response to therapeutic exercise interventions in PD. Improvements in the 10-meter walk, timed-up-and-go, and 30-second sit-to-stand tests were observed over the course of therapy, corresponding to previously reported findings. This study also showed that these improvements were sustained at 13 weeks follow-up.
Accelerometer-derived measures reflected these scores, showing that LSVT BIG significantly improved gait speed, but had no effect on balance or dexterous/fine motor control. In particular, by deconstructing the gait cycle its constituent time phases, significant reductions in step, stride, swing, and stance times were observed with therapy. While these times were also accompanied by significantly lower step counts, indicative of longer step lengths, LSVT BIG showed no effect on gait regularity or stride variability. Significantly higher Sit-to-Stand counts were also matched by a significant reduction in the average, sit-to-stand, full stance, and stand-to-sit times. Together these demonstrated a rescaling of the speed-amplitude relationship in individuals with PD following LSVT BIG.
How might this impact occupational therapists or physiotherapists who are working with people with Parkinson’s disease?
The insights gained from the accelerometer-derived measures can provide clinicians with information about the efficacy of high-amplitude movement therapies, such as LSVT BIG, and can be used to target patients with specific subtypes of Parkinson’s Disease that are more likely to respond to a high-amplitude therapy program. Additionally, this study may encourage therapists to adopt wearable technology when assessing and monitoring their clients. As demonstrated in this study, features of gait and balance not captured by conventional clinical scores can be illustrated on a continuous numerical range (as opposed to ordinal number scale), allowing those with PD to track subtle improvements in their progression.
Were there any surprises or key things you learned?
We were surprised to see that in contrast to the large amplitude tests, LSVT BIG showed no effect on any measure of the quiet stance nor finger-tapping tasks. There has been limited evidence suggesting that LSVT BIG may improve balance based on the results of Berg Balance tests. However, no consistent improvement was observed for any quantitative measure of postural sway in our study. Although targeted at large-amplitude movements, it was also considered that the subject-oriented functional tasks, such as buttoning a shirt or playing piano, may have contributed to slight improvements in dexterous motor control. Given the lack of any observable improvement in finger tapping measures, it remains unclear whether LSVT BIG benefits upper limb motor function in PD. A focus on postural stability and on dexterity may be needed in addition to, or to be incorporated in, the LSVT BIG.
Furthermore, it was surprising to see from our analysis that despite significant improvements in gait speed, no consistent improvement in gait regularity or stride variability was observed in the 10-meter walk test. It may be possible that adaptations in gait regularity and variability may become more evident in alternative walking tasks, such as the 6-minute walking test.
What is happening next in terms of your research on LSVT BIG?
Opportunities exist for developments in therapeutic interventions and further research on LSVT BIG. A larger participant cohort with greater longitudinal follow-up at 6 months or 24 months would likely yield a greater impact for clinical practice. Additionally, it would be beneficial to contrast the performance of participants in the ‘ON’ and ‘OFF’ levodopa states.
Technological advancements offer possibilities for delivering LSVT BIG more easily at home, overcoming the need to attend the rehabilitation clinics. This may be achieved through the development of smartphone apps that employ artificial intelligence to automatically detect and analyze participant movement during LSVT BIG exercises, as well as levels of general activity in daily life. In conjunction with establishing minimal clinically important differences for wearable sensor data, such training apps could facilitate a substantial amount of the cueing needed to engage people with PD in their LSVT BIG programs. This could start by monitoring the daily homework sessions and later develop into replacing the therapist for at least a number of the therapeutic sessions. This would relieve the fiscal burden of 16 face to face sessions, and lessen the geographic need for transportation to and from the clinics. A smartphone-based technology could also facilitate wider access to LSVT BIG for people currently unable to access a therapist due to geographic, financial, or clinician availability perspectives.
The possibilities of monitoring people with PD with wearable sensors presents new possibilities for investigating levels of engagement in activities of daily living, prior to, throughout, and after LSVT BIG. By identifying substantial reductions in activity levels or marked changes in patterns of motor function, wearable sensors could identify when patients need to return to the therapist or neurologist. This could aid physicians to prescribe treatment in response to objective data rather than relying on subjective reports from patients themselves or observations taken during brief hospital appointments. Better use could then be made of clinical appointments, scheduling them in response to clinical need rather than spending them on a regularly timed follow-on to monitor the progress of PD when it was less needed. Home monitoring might be implemented using one or two monitors preplaced during attendance to scheduled appointments or worn in garments designed for that purpose. For such an approach to be useful, data from sensors will have to be linked to functional outcomes for people with PD, to establish a link between therapeutic intervention and functional gains.
