Auditory and visual cueing modulate cycling speed of older adults and persons with Parkinson’s disease in a Virtual Cycling (V-Cycle) system

This study used a cross sectional design. Eligible participants consisted of persons with PD and age-matched healthy adults. The Institutional Review Board at the New York Institute of Technology and Rutgers University School of Health Professions approved this work. All participants provided written informed consent prior to participation.

The virtual reality cycling system V-CYCLE, consists of an evidenced-based custom designed VE, computer, projector display of the VE on a screen, desktop speakers, upright stationary bicycle, revolutions per minute (RPM) sensor, and heart rate monitor.

The VE was built specifically for this study using the free version of Unity 4.3™. Factors embedded in a VE can facilitate or hinder motor behavior [49]. Therefore elements in the V-CYCLE environment were chosen after careful review of the literature and based on their ability to influence self-perception of motion.

The scenery, consisting of a road, mountains, trees and sky, was designed using the default terrain editor of Unity 4.3 with a first person perspective view (Fig. 1). The goal of the design process was to create an open straight road surrounded by mountains with an adequate field of view and variability in the scenery.

The models and avatars used during the design were purchased or downloaded from the Unity asset store. Rendering was done using the built in renderer for terrain, and Skybox for the clouds and sky. The input manager was used to accept keyboard controls for pausing, quitting, and manual override functions for control of the avatar. Scripts within Unity were written in C++ to customize and have control over the VE during the trial. The RPM (Wahoo RPM sensor) and heart rate (Polar HR7) data were collected and recorded independent of Unity using a Wahoo SDK and saved as a.CSV file. This file was used to read the pedal RPM data from the Wahoo sensor to control the speed of the rider. The linear distance covered by the bike/minute in the VE was calculated as (2π * radius of wheel) * RPM. The status of data collection and timer was controlled using a C++ script. The virtual environment utilizes the RPM data from the. CSV output file to control the speed of the avatar in the VE in which 6′ of pedaling corresponds to 3′ of distance in the VE.

Auditory cueing was provided by a metronome set at a rate 20 % higher than the cycling speed of the subject. The 20 % rate was based on the walking literature [52, 53] as well as preliminary trials performed by the investigators on three healthy and three persons with PD to determine a physiological upper limit of pedaling rate. Visual cueing was in the form of central road markers in the VE, scaled to represent a real road.

An upright stationary bicycle (Cybex model #750C) was used in this study. A Wahoo cadence sensor attached to the crank of the bike pedal measured the pedal RPM and transferred the data via Bluetooth™. An Epson (Model 485Wi) short throw projector was used to project the environment onto a flat wall, approximately 5 ft in front of the bicycle, resulting in an equivalent screen size of 94-in. (43 X 83 in.) with a horizontal field of view of 80° (Fig. 2). A pair of Logitech desktop speakers connected to an IPhone metronome application was used for trials with audio cueing.

Twenty-eight participants, 15 people with PD (66.3 +/− 9.6 years; Hoehn &Yahr (H&Y) stages II and III) [54] and 13 age-matched healthy adults (66.7 +/− 9.1, years), voluntarily participated in the study. Participants were recruited through flyers, referral, and exercise groups. Age-matched healthy adults were spouses or friends of participants with PD. Telephone or in-person interviews were used to screen for eligibility. Participants were included if they were 50 to 85 years inclusive, able to ride a stationary upright bicycle and had a Montreal Cognitive Assessment (MoCA) [55] score >/= 24. Participants with PD were included if they were diagnosed by a neurologist as having PD and were in stage 2–3 H&Y [54]. Participants were excluded if they had: 1. severe hearing or visual deficit including color blindness; 2. history of stroke, traumatic brain injury or neurological disorder other than PD; 3. unstable medical condition including musculoskeletal disorders such as severe arthritis, knee surgery, hip surgery; or any other condition that the investigators determine would impair the ability to ride a stationary bicycle; 4. medical or musculoskeletal contraindications to exercise. Participants with PD were excluded if they had incapacitating tremors or dyskinesias that would limit ability to ride a stationary bicycle.

Participants attended two testing sessions lasting approximately 1 h each. The first session characterized the participants by measuring: age, gender, mental status, and lower extremity range of motion. Participants with PD were clinically rated by a trained examiner on the H&Y scale [54] and the Motor subsection (part III), of the Unified Parkinson’s Disease Rating Scale (UPDRS) [56].

The second session consisted of the bicycling protocol. Participants were seated on the bicycle with the seat height adjusted between 100 % and 110 % of the length from the greater trochanter to the floor (measured without shoes) [57]. After a 5-min warm-up, participants performed 9 trials (1 min each) of cycling divided into two blocks, Auditory (4 trials) and Visual (5 trials) (See Tables 1 and 2 for the description of trials). Each block included a baseline condition (cycling without a VE or cues) to ensure that pedaling rate changes were assessed relative to each block. Block order was counterbalanced between participants. To ensure the same frame of reference from one trial to the next, the order of trials was maintained within each block. This method of trial presentation has been used in similar studies [29].

The 1-min trial length was chosen to capture short-term changes in cycling behavior while minimizing the effects of fatigue on cycling rate. The Borg scale [58] was used as a rate of perceived exertion and was shown to participants immediately after completing a trial. Heart rate was monitored throughout. Readiness to continue to the next trial was determined when heart rate returned to no more than ten beats above the warm up rate. Rest between trials ranged from 1 to 3 min.

The primary outcome measure was pedaling rate measured as RPMs. Pedaling rate was continuously recorded via a Bluetooth cadence sensor attached to the crankshaft of the pedal. Average cadence over the 1-min trial was calculated and used for data analysis. The first 5 s of each trial were not included in the analysis to allow participants to stabilize their cycling rate.

Descriptive analyses were performed on patient characteristics: age, gender, cognitive status, disease stage, and motor assessment. Differences between groups for baseline characteristics were tested with independent t-tests. Means and standard deviations were calculated for RPM with an alpha level of 0.05 and corrected for multiple planned comparisons using a Bonferroni correction.

Fifteen persons with PD and 13 age-matched healthy adults participated in the study. There were no significant differences in age or cognitive status between the two groups (Table 3). Participants with PD were in stage 2 or 3 on the H&Y scale [54].

There was a significant main effect for cue, with no group or interaction effects. Age-matched healthy adults pedaled at a faster, albeit non-significant, rate than persons with PD in all conditions. Within group comparisons showed that both groups significantly increased their pedaling rate in the Auditory Condition (F = 24.72, df 1.7 p < 0.000). Compared to baseline, both groups increased their pedaling rate with the presentation of auditory cues; persons with PD, p < 0.000; age matched healthy adults, p < 0.000, and when auditory cues were presented with the VE; persons with PD: p < 0.000; age matched healthy adults p < 0.002. Persons with PD responded with an increase in pedaling rate to the presentation of the VE compared to baseline (p < 0.000) whereas the age-matched healthy adults did not (p = 0.017) (Figs. 3 and 4). Expected and observed changes in cycling speed are presented in Table 4.

There was a significant main effect for cue, with no group or interaction effects. Age-matched healthy adults pedaled at a faster rate than persons with PD in all conditions showing a trend toward significance (F = 4.00, df 1, p = .056). Within group comparisons showed that both groups significantly increased their pedaling rate (F = 40.69, df 4, p < 0.000). Comparisons within trials exclusive of baseline revealed that age-matched healthy adults increased their pedaling rate with each successive trial, but persons with PD increased their pedaling rate only when explicitly instructed to attend to the cues (p = 0.000) (Figs. 5 and 6).

The expected and observed changes in pedaling rate are presented in Table 5. The largest increase in pedaling rate for both groups (PD, 35 % and age-matched healthy adults, 25 %) was in the VE + VC 20 % with instruction condition.

The main findings in the auditory condition are that persons with PD and age-matched healthy adults increased their pedaling rate compared to baseline, and there was no interference effect when the auditory cues were presented with the VE. The increase in pedaling rate in both groups agrees with our hypothesis and aligns with the literature that healthy people can match their walking speed to an auditory cue [53, 59‐61]. However, in contrast to the walking literature, there was no interference for either group when the VE and auditory cues where presented simultaneously [48].

The lack of interference found in this study may be attributed to a variety of reasons. First, elements in the periphery of a VE provide important peripheral cues that help increase immersion of the user in the environment. These cues also are also known to increase self-perception of motion [49]. The stimulus in this environment may have been weak due to a lack of peripheral cues and thus no interference effect was found. Alternatively, this finding may be explained by general differences between walking and cycling. In walking, one receives proprioceptive information regarding position while translating through space. This information contributes to muscle coordination and plays a role in the automaticity of walking [62]. During stationary cycling, there is no translation, and therefore proprioceptive inputs and response to these inputs may differ. A second explanation is that in cycling, angular momentum of the pedaling apparatus may keep the legs moving along [18] thereby off-setting any slowing down in pedaling rate from the VE. Lastly, there may have been an order effect due to the non-randomization of trials within each block. Participants heard the auditory cue in the first trial and may have continued to attend to it when the VE was presented.

Both persons with PD and age-matched healthy adults increased their pedaling rate in most trials compared to baseline. Their patterns however, differed. Persons with PD significantly increased their pedaling rate with just the viewing of the VE but age-matched healthy adults did not. This is in agreement with our hypothesis and the literature that states persons with PD are more reliant on visual stimuli [46]. The stimulus of the optic flow with the VE alone stimulated a higher cycling rate for persons with PD and not age-matched healthy adults.

Persons with PD responded to the visual cues only when explicitly instructed to attend to the cues and not in the implicit cue conditions. The use of explicit instructions to augment motor performance is well demonstrated in the PD literature [5, 63]. Morris et al, in 1996 investigated the effects of visual cue training on the ability to walk to normal gait parameters [63]. Normalization of gait was found when subjects were explicitly instructed to attend to the markers, “step over the markers and walk to the end of the walkway”. Similarly, van Wegen et al., found that explicit instruction to attend to visual cues modulated stride frequency while maintaining walking velocity in persons with PD [29]. Our findings, and the evidence in the literature, have implications for adding explicit messages into a VE to increase the likelihood of achieving the target motor behavior.

As expected, age-matched healthy adults responded to progressively faster visual cues, while persons with PD did not. This may be because the increase in optic flow speed preferentially influenced pedaling rate in age-matched healthy adults. This finding is in agreement with the literature that states that decreasing the spatial frequency between objects in a VE gives the impression of moving faster through the environment [24, 50]. This finding also suggests that stimuli in the VE alone may not have been salient enough to produce a response in persons with PD. Alternatively, unless explicitly instructed to attend to a cue, persons with PD were not able to process the stimuli fast enough.

Contrary to our hypothesis, age-matched healthy adults did not pedal significantly faster than persons with PD in either the auditory or the visual condition. This may be explained in part by the high functioning persons with PD that were studied. The difference in the performance under the visual condition approached significance, with age-matched healthy adults pedaling faster than persons with PD. However, the percent change from baseline was greater for persons with PD.