Effects of 8 weeks of balance training, virtual reality training, and combined exercise on lower limb muscle strength, balance, and functional mobility among older men: a randomized controlled trial

Background: Poor muscle strength, balance, and functional mobility have predicted falls in older adults. Fall prevention guidelines recommend highly challenging balance training modes to decrease falls; however, it is unclear whether certain modes are more effective. The purpose of this study was to determine whether traditional balance training (BT), virtual reality balance training (VR), or combined exercise (MIX) relative to a waitlist control group (CON) would provoke greater improvements in strength, balance, and functional mobility as falls risk factor proxies for falls in older men. Hypothesis: We hypothesized that 8 weeks of MIX will provoke the greatest improvements in falls risk factors, followed by similar improvements after BT and VR, relative to the CON. Study design: Single-blinded randomized controlled trial NCT02778841 (ClinicalTrials.gov identifier). Level of evidence: Level 2. Methods: In total, 64 community-dwelling older men (age 71.8 ± 6.09 years) were randomly assigned into BT, VR, MIX, and CON groups and tested at baseline and at the 8-week follow-up. The training groups exercised for 40 minutes, 3 times per week, for 8 weeks. Isokinetic quadriceps and hamstrings strength on the dominant and nondominant legs were primary outcomes measured by the Biodex Isokinetic Dynamometer. Secondary outcomes included 1-legged stance on firm and foam surfaces, tandem stance, the timed-up-and-go, and gait speed. Separate one-way analyses of covariance between groups were conducted for each outcome using baseline scores as covariates. Results: (1) MIX elicited greater improvements in strength, balance, and functional mobility relative to BT, VR, and CON; (2) VR exhibited better balance and functional mobility relative to BT and CON; and (3) BT demonstrated better balance and functional mobility relative to CON. Conclusion: The moderate to large effect sizes in strength and large effect sizes for balance and functional mobility underline that MIX is an effective method to improve falls risk among older adults

The Sensor Technology and Rehabilitative Timing (START) Protocol: A Randomized Controlled Trial for the Rehabilitation of Mild Traumatic Brain Injury

BACKGROUND: Clinical practice for rehabilitation after mild traumatic brain injury (mTBI) is variable, and guidance on when to initiate physical therapy is lacking. Wearable sensor technology may aid clinical assessment, performance monitoring, and exercise adherence, potentially improving rehabilitation outcomes during unsupervised home exercise programs. OBJECTIVE: The objectives of this study were to: (1) determine whether initiating rehabilitation earlier than typical will improve outcomes after mTBI, and (2) examine whether using wearable sensors during a home-exercise program will improve outcomes in participants with mTBI. DESIGN: This was a randomized controlled trial. SETTING: This study will take place within an academic hospital setting at Oregon Health & Science University and Veterans Affairs Portland Health Care System, and in the home environment. PARTICIPANTS: This study will include 160 individuals with mTBI. INTERVENTION: The early intervention group (n = 80) will receive one-on-one physical therapy 8 times over 6 weeks and complete daily home exercises. The standard care group (n = 80) will complete the same intervention after a 6- to 8-week wait period. One-half of each group will receive wearable sensors for therapist monitoring of patient adherence and quality of movements during their home exercise program. MEASUREMENTS: The primary outcome measure will be the Dizziness Handicap Inventory score. Secondary outcome measures will include symptomatology, static and dynamic postural control, central sensorimotor integration posturography, and vestibular-ocular-motor function. LIMITATIONS: Potential limitations include variable onset of care, a wide range of ages, possible low adherence and/or withdrawal from the study in the standard of care group, and low Dizziness Handicap Inventory scores effecting ceiling for change after rehabilitation. CONCLUSIONS: If initiating rehabilitation earlier improves primary and secondary outcomes post-mTBI, this could help shape current clinical care guidelines for rehabilitation. Additionally, using wearable sensors to monitor performance and adherence may improve home exercise outcomes

Validation of an Inertial Sensor Algorithm to Quantify Head and Trunk Movement in Healthy Young Adults and Individuals with Mild Traumatic Brain Injury

Wearable inertial measurement units (IMUs) may provide useful, objective information to clinicians interested in quantifying head movements as patients’ progress through vestibular rehabilitation. The purpose of this study was to validate an IMU-based algorithm against criterion data (motion capture) to estimate average head and trunk range of motion (ROM) and average peak velocity. Ten participants completed two trials of standing and walking tasks while moving the head with and without moving the trunk. Validity was assessed using a combination of Intra-class Correlation Coefficients (ICC), root mean square error (RMSE), and percent error. Bland-Altman plots were used to assess bias. Excellent agreement was found between the IMU and criterion data for head ROM and peak rotational velocity (average ICC > 0.9). The trunk showed good agreement for most conditions (average ICC > 0.8). Average RMSE for both ROM (head = 2.64°; trunk = 2.48°) and peak rotational velocity (head = 11.76 °/s; trunk = 7.37 °/s) was low. The average percent error was below 5% for head and trunk ROM and peak rotational velocity. No clear pattern of bias was found for any measure across conditions. Findings suggest IMUs may provide a promising solution for estimating head and trunk movement, and a practical solution for tracking progression throughout rehabilitation or home exercise monitoring

Center of pressure (CoP) range, root mean square (RMS) and velocity in the medial-lateral (ML) and anterior-posterior (AP) directions during repetitive bilateral reaching task for 30 s and 120 s in controls, as well as non-freezers and freezers on and off medication.

<p>Center of pressure (CoP) range, root mean square (RMS) and velocity in the medial-lateral (ML) and anterior-posterior (AP) directions during repetitive bilateral reaching task for 30 s and 120 s in controls, as well as non-freezers and freezers on and off medication.</p

Number of reaching cycles, cycle asymmetry and coefficient of variation (CV) for the less and more affected side during a repetitive bilateral reaching task in controls and individuals with Parkinson’s disease (PD) on and off medication.

<p>Number of reaching cycles, cycle asymmetry and coefficient of variation (CV) for the less and more affected side during a repetitive bilateral reaching task in controls and individuals with Parkinson’s disease (PD) on and off medication.</p

Number of reaching cycles, cycle asymmetry and coefficient of variation (CV) for the less and more affected side during a repetitive bilateral reaching task in controls, as well as non-freezers and freezers on and off medication.

<p>Number of reaching cycles, cycle asymmetry and coefficient of variation (CV) for the less and more affected side during a repetitive bilateral reaching task in controls, as well as non-freezers and freezers on and off medication.</p

Center of pressure (COP) range, root mean square (RMS) and velocity in the medial-lateral (ML) and anterior-posterior (AP) directions during repetitive bilateral reaching task for 30 s and 120 s in controls and individuals with Parkinson’s disease (PD) on and off medication.

<p>Center of pressure (COP) range, root mean square (RMS) and velocity in the medial-lateral (ML) and anterior-posterior (AP) directions during repetitive bilateral reaching task for 30 s and 120 s in controls and individuals with Parkinson’s disease (PD) on and off medication.</p

Standing repetitive pointing task in individuals with and without Parkinson's disease

<p>[ These data refer to a manuscript currently under revision in PlosOne. In this MS we aimed to determine the effects of levodopa medication on the performance of a repetitive pointing task while standing, and to investigate the optimal trial duration in individuals with Parkinson’s disease, and older adults. Seventeen individuals with Parkinson’s disease (5 freezers) and 9 older adults stood on force platforms for 30 s and 120 s while performing a bilateral repetitive pointing task, tracked by motion capture. Participants with Parkinson’s disease were assessed on and off medication and older adults were also assessed on separate days. The main findings were that: 1) on medication, participants with Parkinson’s exhibited greater center of pressure root mean square in the medial-lateral direction, greater velocity in the medial-lateral and anterior-posterior directions, and greater range in the medial-lateral direction than off medication; 2) longer trial durations resulted in greater center of pressure range in the medial-lateral and anterior-posterior directions and greater coefficient of variation in finger pointing on the least affected side; 3) Parkinson’s participants exhibited larger range in the medial-lateral direction compared to older adults; 4) off medication, freezers presented with less range and root mean square in the anterior-posterior direction than non-freezers; and 5) a correlation emerged between the freezing of gait questionnaire and pointing asymmetry and the coefficient of variation of pointing on the most affected side. Therefore, Parkinson’s medication may increase instability during a repetitive pointing task. Longer trials may provide a better depiction of sway by discriminating between those with and without neurological impairment. Individuals with Parkinson’s were less stable than older adults, supporting that they are at a greater risk for falls. The greater restrictive postural strategy in freezers compared to non-freezers is likely a factor that augments fall-risk. Lastly, the link between freezing of gait and upper-limb movement indicates that freezing may manifest first in the lower-limbs. Add description ]</p