Balance Training With a Vibrotactile Biofeedback System Affects the Dynamical Structure of the Center of Pressure Trajectories in Chronic Stroke Patients

Even with all this previous research NO ONE seems able to write a protocol on this. Incompetency reigns supreme and the result is stroke survivors don't recover. Hope you are ok with that. 

• vibrotactile (1)
• vibrotactile feedback (4)

 

Balance Training With a Vibrotactile Biofeedback System Affects the Dynamical Structure of the Center of Pressure Trajectories in Chronic Stroke Patients

Kentaro Kodama^1†, Kazuhiro Yasuda^2*†, Nikita A. Kuznetsov³, Yuki Hayashi⁴ and Hiroyasu Iwata⁴

• ¹Department of Economics, Kanagawa University, Yokohama, Japan
• ²Research Institute for Science and Engineering, Waseda University, Tokyo, Japan
• ³School of Kinesiology, Louisiana State University, Baton Rouge, LA, United States
• ⁴Graduate School of Creative Science and Engineering, Waseda University, Tokyo, Japan

Haptic-based vibrotactile biofeedback (BF) is a promising technique to improve rehabilitation of balance in stroke patients. However, the extent to which BF training changes temporal structure of the center of pressure (CoP) trajectories(What the fuck is this?) remains unknown. This study aimed to investigate the effect of vibrotactile BF training on the temporal structure of CoP during quiet stance in chronic stroke patients using detrended fluctuation analysis (DFA). Nine chronic stroke patients (age; 81.56 ± 44 months post-stroke) received a balance training regimen using a vibrotactile BF system twice a week over 4 weeks. A Wii Balance board was used to record five 30 s trials of quiet stance pre- and post-training at 50 Hz. DFA revealed presence of two linear scaling regions in CoP indicating presence of fast- and slow-scale fluctuations. Averaged across all trials, fast-scale fluctuations showed persistent dynamics (α = 1.05 ± 0.08 for ML and α = 0.99 ± 0.17 for AP) and slow-scale fluctuations were anti-persistent (α = 0.35 ± 0.05 for ML and α = 0.32 ± 0.05 for AP). The slow-scale dynamics of ML CoP in stroke patients decreased from pre-training to post-BF training (α = 0.40 ± 0.13 vs. 0.31 ± 0.09). These results suggest that the vibrotactile BF training affects postural control strategy used by chronic stroke patients in the ML direction. Results of the DFA are further discussed in the context of balance training using vibrotactile BF and interpreted from the perspective of intermittent control of upright stance.

Introduction

Following a stroke, a complex interplay of sensory, motor, and cognitive impairments may interfere with balance (de Haart et al., 2004). Stroke patients commonly show increased postural sway and asymmetric weight distribution while standing (Mansfield et al., 2013; Hendrickson et al., 2014). Impaired balance decreases mobility and increases fall risk in elderly stroke patients (Lamb et al., 2003). Vibrotactile biofeedback (BF) application to the trunk is a promising method for restoring balance ability (e.g., Dozza et al., 2007; Bechly et al., 2013). However, we previously found that a 4 week vibrotactile BF training did not induce significant changes on several center of pressure (CoP) measures (i.e., sway area, path length) in chronic stroke patients (Yasuda et al., 2018).

In this report, we apply detrended fluctuation analysis (DFA; Peng et al., 1994) to characterize the effects of this BF training in stroke patients. DFA offers an additional perspective on postural control dynamics in comparison to traditional CoP metrics because it examines control processes across multiple time scales (Eke et al., 2002; Seuront, 2009). DFA can evaluate presence of temporal correlations across a range of window sizes (Brown and Liebovitch, 2010). Fractal processes can be categorized in two families: fractional Gaussian noise (fGn) and fractional Brownian motions (fBm). The scaling exponent, DFA α, is interpreted as an indicator of temporal correlation pattern: If 0 < α < 1 (fGn) with anti-persistent (α < 0.5), random (α = 0.5), or persistent dynamics (α > 0.5). If 1 < α < 2 (fBm) with under-diffusive (a < 1.5), Brownian (α = 1.5), hyper-diffusive dynamics (α > 1.5) (Delignières et al., 2011).

Previous studies have indicated that DFA can identify differences in postural control strategy between young and elderly adults (Amoud et al., 2007; Duarte and Sternad, 2008). Roerdink et al. (2006) applied DFA to CoP data to compare stroke patients with healthy elderly and showed that the CoP trajectories of both the healthy elderly and stroke patients exhibited temporally correlated patterns rather than random noise (Roerdink et al., 2006).

The dynamical structure of CoP during quiet stance is characterized by presence of multiple scaling regions (Minamisawa et al., 2009; Teresa Blázquez et al., 2009; Kuznetsov et al., 2013). Kuznetsov et al. (2013) reported three scaling regions in a sample of healthy young adults. Presence of multiple scaling regions may be indicative of intermittent control strategy (Loram et al., 2011) or continuous open- and closed-loop control strategy (Collins and De Luca, 1995).

The effect of vibrotactile BF on the dynamics across multiple-scales for postural control remains unknown however. Postural control strategy used by stroke patients may differ from the strategies used by younger adults or healthy elderly due to freezing, asymmetrical weight distribution, and sensory input alterations. We hypothesized that intensive balance training using vibrotactile BF would affect the dynamical structure of CoP trajectories in chronic stroke patients.

Materials and Methods

Participants

We recruited 9 participants with chronic hemiparetic stroke from the Department of Physical Medicine and Rehabilitation, Tokyo General Hospital (Table 1). Inclusion criteria were positive history of chronic unilateral ischemic or hemorrhagic stroke, age 50–80 years, stroke >6 months ago, completion of conventional therapy, and ability to stand unsupported for 10 min and sense BF system vibrations. Prior to the study, all participants underwent conventional balance rehabilitation with a physical therapist twice a week.

TABLE 1

Table 1. Participants' demographic data (n = 9).

BF System Overview

The vibrotactile BF device consisted of a Nintendo Wii balance board (Nintendo Co., Ltd., Kyoto, Japan) and a personal computer with custom software (Visual Studio; Microsoft Corp., Redmond, WA, USA). CoP position data were measured in both the ML and AP directions at 50 Hz. The system uses vibration motors attached to the belt at the level of the pelvic girdle (bilaterally attached at the anterior superior iliac and posterior superior iliac spine) to convey information about body sway (Figure 1).

FIGURE 1

Figure 1. Biofeedback system overview. Vibrators on the pelvic belts worn by the participants vibrated in the corresponding direction when the center of pressure (CoP) exceeded the predefined threshold (e.g., if CoP shifts to the back left, the back left vibrator is activated).

Protocol and Postural Task

Participants underwent 45 min of BF training 2 times per week for 2 weeks. The training consisted of two task-oriented balance training exercises used as part of the conventional rehabilitation (Teasell et al., 2008).

Two balance training exercises were used: (1) standing on a rubber foam mat (balance mat, Sanwa Kako Co. Ltd, Japan): participants stood barefoot on the mat with their eyes open and were instructed to use the BF information to stabilize their postural sway (i.e., they were instructed to stay within the predefined threshold area using BF information) and (2) weight-shifting to the paralyzed limb: participants were instructed to move their paralyzed lower limb forward and then put their weight on that limb. While doing so, participants used the BF information to help maintain a stable standing position. Each training session comprised 10 repetitions of the balance task (1 min per repetition, 10 min total) with a short interval between repetitions. The BF threshold setting was reset on each day of training before implementing tasks (1) and (2). We determined the circular threshold as a 95% confidence circle area (Yasuda et al., 2017) during the 30 s stance. Target area was defined as 90% of the pre-measured 95% confidence circle area. The BF vibrators were activated when the CoP exceeded this threshold (Yasuda et al., 2017).

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