Background
‘The competence of an individual to have the physiological capacity to perform normal everyday activities safely and independently without undue fatigue’ [
1] signifies the functional abilities of an individual. Disability, defined as difficulty or dependency in the execution of the activities of daily living, is associated with increased healthcare utilization and related costs [
2]. Disability in frail older people is considered a public health problem [
3] in which prevention has to be considered a priority for research and clinical practice [
4]. Physical activity (PA) for the elderly is one of the major elements for general health prevention [
5]; therefore inactive or sedentary elderly should increase their PA [
6]. Despite the known benefits of PA, residents living in long-term care (LTC) are relatively sedentary [
7,
8].
The loss of muscle mass and strength with age, coined sarcopenia, is recognized as a major cause of disability and morbidity in the elderly [
9]. Sarcopenia describes the progressive decline in skeletal muscle mass and function (strength or performance) with advancing age [
10]. However, recent studies demonstrated that muscle atrophy is a relatively small contributor to the loss of muscle strength [
11‐
13]. Changes in neurologic function and/or the intrinsic force-generating properties of skeletal muscle are recently proposed to be responsible for muscle weakness and motor dysfunction in the elderly [
11,
14‐
18]. Dynapenia has been used to coin this age-associated loss of muscle strength and power with its significant clinical consequences; e.g., the increased risk for functional limitations, disability, and mortality. Dynapenia encompasses broader aspects of skeletal muscle performance, and so includes strength (i.e., maximal voluntary force) and/or mechanical power (a product of force - time velocity) [
19] together with aspects of neurological functioning [
20,
21].
Both neurologic and skeletal muscle properties are necessary for optimal muscle force production and control [
16,
17,
22]. The nervous system’s ability to fully activate a skeletal muscle voluntarily for example seems to be impaired in individuals with dynapenia [
23]. Furthermore, poor sensorimotor nerve function independently predicts mobility disability [
24]. Targeting neural structures through exercise is, therefore, considered important in influencing muscle strength in elderly [
25].
Efficient movement function and the maintenance of balance function during dynamic tasks; e.g., during walking, are more complex than merely adequate force production from the muscles [
26]. For whole body movements it is important to precisely coordinate muscle actions. This requires sensory, biomechanical and motor-processing strategies along with learned responses from previous experiences and anticipation of change [
27,
28]. Adequately combining three levels of motor control (spinal reflex, brain stem balance, and cognitive programming) produces appropriate muscle responses [
29]. So, from these results, it can be hypothesised that when focusing on these three levels of motor control in a training program there will be improvements in muscle recruitment and timing and, hence, physical functioning and muscle strength.
Stochastic resonance (SR) is a phenomenon in nonlinear systems characterized by a response increase of the system induced by a particular level of input noise [
30,
31]. One of the first studies applying noise in humans revealed increased sensitivity to detect sub-threshold tactile stimuli as an effect to such an intervention [
32]. Cordo and colleagues [
33] were among the first to demonstrate that the application of noise on human muscle spindle receptors improved afferents sensitivity in the human motor system and suggested, based on their results, that a stochastic-resonance based technique could be applied in clinical settings to individuals with elevated cutaneous thresholds; e.g., to older adults [
33]. First evidence that mechanical noise applied to the feet via vibrating insoles improved balance in standing position stems from Pripatla et al. [
34] and Collins and co-workers [
35]. Systematic reviews concluded that, compared to more demanding interventions, whole-body vibration (WBV) as a sensorimotor training might be a safer and less fatiguing type of exercise [
36] with a beneficial effect on movement skills [
37] and muscle strength [
38]. Stochastic resonance whole-body vibration (SR-WBV) has been described as stimulating sensorimotor processes [
31,
39] with a positive effect on muscle functional strength [
38]. The SR-WBV stimulus triggers muscle spindles and, thereby, improves the functionality of the muscle-nerve system [
40] and adjusts afferent and efferent signals which, in turn, are leading to “training” effects for the sensorimotor system [
41]. Muscle strength increase following SR-WBV is mainly attributed to neural adaptation bringing on improvements in inter- and intra-muscular coordination [
42]. See [
43] for an overview. Virtual reality training techniques may be used to incorporate cognitive programming elements into exercise [
44] and could, hence, also be part of a training program for elderly [
45]. Pilot trials with long term care dwelling elderly showed beneficial effects on physical performance for those adhering to an SR-WBV intervention, however, the program requires modifications that target improved compliance with the intervention [
46]. Interventions performed with frail individuals often suffer from low adherence rates and are, therefore, advised to specifically include support and motivation strategies, as well as giving assistance to individuals to develop both goals and the strategies to achieve these [
47,
48].
The aim of this study was to assess the effects of a sensorimotor training program with SR-WBV & Virtual Reality Training that was accompanied with motivational instructions in LTC elderly on lower extremity physical function and leg muscle properties. We hypothesised that an intervention program that targets motor control will effect on physical functioning and muscle strength of LTC elderly.
Results
From the 40 LTC elderly approached, 31 agreed to participate (Fig.
1) resulting in a 77.5 % recruitment rate for the sampling frame. One participant from SG died before baseline measurement and eight of the 40 initially deemed eligible were willing to participate, however, did not fulfill the inclusion criteria (
n = 3 low MMSE score;
n = 4 with recent stroke;
n = 1 with multiple sclerosis,
n = 1 with parkinson disease). Training adherence rate, expressed in %; [100 ÷ (34 ÷ Mean amount of trainings visited)] revealed a mean attendance rate of 100 % (34 of 34 intervention sessions).
The participants were willing to be randomized. Neither subjective nor objective side-effects related to the used intervention were reported. At baseline, no statistically significant differences (p < 0.05) were found between groups.
Table
2 presents the primary and secondary outcomes at baseline. All SPPB data could be used for statistical analysis while for strength values an ITT was perfomed. The time force-curve of four participants could not be used for analysis. Fsub values and IRFDsub are listed in Additional files
1,
2,
3,
4,
5,
6,
7 and
8. At baseline no group differences were identified.
Table 2
SPPB ANOVA with repeated measurements (ranks) intergroup-by-time effects and group-by-time interaction
SPPB Total (time effects) | 0.22 | 0.30 | 0.742 | 0.22 |
SPPB Total (interaction effects) | 0.60 | 10.20 | 0.001* | 0.60 |
Primary outcome: short physical performance battery
A significant interaction effect in SPPB; F(1.7,48) = 35.2,
p < 0.001) with a large ES (η2 = 0.557) were determined in favour of IG (Table
2). The between group effect (Table
5) shows significant values after 4 weeks F(1,28 = 6.85; η2 = 0.20;
p = 0.014) and after 8 weeks F(1,28 = 13.17; η2 = 0.32;
p = 0.001) in favour of IG.
Table 3
ANOVA with repeated measurements (ranks) intergroup-by-time effects and group-by-time interaction for the secondary outcomes IMVC (N)
IMVC right ex (N) (time effects) | 0.001 | 0.006 | 0.994 | 0.001 |
IMVC right ex (N) (interaction effects) | 0.28 | 5.41 | 0.01* | 0.28 |
IMVC left ex (N) (time effects) | 0.01 | 0.007 | 0.993 | 0.001 |
IMVC left ex (N) (interaction effects) | 0.34 | 7.16 | 0.003* | 0.51 |
IMVC right flex (N) (time effects) | 0.27 | 1.62 | 0.232 | 0.27 |
IMVC right flex (N) (interaction effects) | 0.001 | 0.003 | 0.997 | 0.001 |
IMVC left flex (N) (time effects) | 0.15 | 2.54 | 0.097 | 0.15 |
IMVC left flex (N) (interaction effects) | 0.001 | 0.001 | 0.999 | 0.001 |
| 0.09 | 1.33 | 0.282 | 0.09 |
Secondary outomes: strength tests
Tables
3,
4 and
5 summarise the intervention effects for the muscle strength related outcomes. IMVC showed significant changes over time for knee extension right and left and knee flexion right (Table
4). Post-hoc analysis revealed significant between group effects for knee flexion left (
p < 0.02) after eight weeks of training (Table
5).
Table 4
ANOVA with repeated measurements (ranks) intergroup-by-time effects and group-by-time interaction for the secondary outcomes IRFD (N/ms)
IRFD right ex (N/ms) (time effects) | 0.001 | 0.005 | 0.995 | 0.001 |
IRFD right ex (N/ms) (interaction effects) | 0.238 | 4.37 | 0.022* | 0.24 |
IRFD left ex (N/ms) (time effects) | 0.43 | 10.73 | 0.001* | 0.43 |
IRFD left ex (N/ms) (interaction effects) | 0.02 | 0.03 | 0.97 | 0.002 |
IRFD right flex (N/ms) (time effects) | 0.68 | 29.38 | 0.001* | 0.68 |
IRFD right flex (N/ms) (interaction effects) | 1.45 | 6.30 | 0.007* | 0.59 |
IRFD left flex (N/ms) (time effects) | 0.85 | 52.61 | 0.001* | 0.85 |
IRFD left flex (N/ms) (interaction effects) | 0.52 | 9.65 | 0.001* | 0.52 |
Table 5
Between group effects at BASE, 4 W and 8 W on SPPB, IMVC and IRFD
SPPB (Score) (IG) | 2.9 ± 1.7 | 0.16/0.07 | 5.6 ± 2.9 | 0.01*/0.21 | 7.13 ± 3.2 | 0.004*/0.26 |
SPPB (Score) (SG) | 3.9 ± 1.5 | | 3.4 ± 1.2 | 3.7 ± 1.2 |
IMVC right ex (N) (IG) | 136.0 ± 58.4 | 0.62/0.01 | 138.4 ± 56.0 | 0.81/0.002 | 180.1 ± 71.2 | 0.10/0.09 |
IMVC right ex (N) (SG) | 157.9 ± 75.7 | | 134.4 ± 59.0 | 147.8 ± 62.8 |
IMVC left ex (N) (IG) | 140.4 ± 89.3 | 0.97/0.001 | 163.1 ± 78.1 | 0.12/0.08 | 194.6 ± 90.2 | 0.04°/0.26 |
IMVC left ex (N) (SG) | 132.5 ± 56.0 | | 119.5 ± 54.0 | 126.1 ± 65.7 |
IMVC right flex (N) (IG) | 61.0 ± 29.0 | 0.88/0.001 | 74.4 ± 30.7 | 0.29/0.04 | 87.0 ± 38.5 | 0.08/0.11 |
IMVC right flex (N) (SG) | 64.1 ± 31.0 | | 67.0 ± 31.7 | 67.0 ± 31.2 |
IMVC left flex (N) (IG) | 73.5 ± 42.6 | 0.37/0.03 | 79.0 ± 44.8 | 0.15/0.07 | 86.9 ± 36.8 | 0.03°/0.15 |
IMVC left flex (N) (SG) | 60.3 ± 24.5 | | 60.4 ± 25.3 | 64.4 ± 16.5 |
IRFD right ex (N/ms) (IG) | 0.46 ± 0.3 | 0.70/0.005 | 0.56 ± 0.3 | 0.02*/0.06 | 0.72 ± 0.4 | 0.004*/0.25 |
IRFD right ex (N/ms) (SG) | 0.41 ± 0.3 | | 0.40 ± 0.2 | 0.39 ± 0.1 |
IRFD left ex (N/ms) (IG) | 0.48 ± 0.4 | 0.97/0.001 | 0.69 ± 0.5 | 0.02*/0.19 | 0.82 ± 0.5 | 0.001*/0.41 |
IRFD left ex (N/ms) (SG) | 0.38 ± 0.3 | | 0.34 ± 0.1 | 0.29 ± 0.1 |
IRFD right flex (N/ms) (IG) | 0.13 ± 0.1 | 0.14/0.08 | 0.25 ± 0.1 | 0.01*/0.23 | 0.39 ± 1.5 | <0.001*/0.64 |
IRFD right flex (N/ms) (SG) | 0.19 ± 0.1 | | 0.15 ± 0.1 | 0.15 ± 0.1 |
IRFD left flex (N/ms) (IG) | 0.17 ± 0.1 | 0.97/0.001 | 0.26 ± 0.2 | 0.02*/0.19 | 0.39 ± 0.2 | <0.001*/0.42 |
IRFD left flex (N/ms) (SG) | 0.15 ± 0.1 | | 0.14 ± 0.1 | 0.15 ± 0.1 |
Following eight weeks of SR-WBV and DVG training, Fsub measures at 30 ms, 100 ms and 200 ms in both right and left leg flexion showed a significant between group effect (
p < 0.01) with large ES (>0.14) compared to Sham intervention (Additional files
1,
2,
3,
4,
5,
6,
7 and
8).
Table
3 shows the Greenhouse-Geisser univariate test results; a significant intragroup-by-time effect and group-by-time interaction effect following eight weeks of SR-WBV and DVG intervention on IRFD. Significant between groups effects were both seen after 4 weeks (
p < 0.05) and 8 weeks (
p < 0.05) in IRFD right and left leg extension and right and left leg flexion manoeuvres (Table
5).
Significant effects (
p < 0.001) and large ES > 0.14 in the right and left leg knee extension and knee flexion movements were shown for IRFDsub at 0-30 ms, 0-50 ms, 0-100 ms and 100-200 ms (Additional files
9,
10,
11,
12,
13,
14,
15 and
16).
Discussion
This study aimed to assess the effects of SR-WBV & Video Dance Game Training that was accompanied with motivational instructions in LTC elderly on lower extremity physical function and leg muscle properties. We hypothesised that an intervention program that targets motor control will effect on physical functioning and muscle strength levels of LTC elderly. The results of the study demonstrate that a combination of SR-WBV and DVG may be used as a skilling-up exercise for LTC elderly because of significant SPPB score change values in IG (+58.8 %) compared to SG (− 4.0 %) and concomitant significant strength improvements seen in Fsub, IRFD, and IRFDsub in IG compared to SG.
Coaching the LTC participants in both groups with a professional exercise instructor to enhance exercise participation, aimed to ensure that the targeted exercise frequencies and levels would be reached, and to prevent attrition. This approach showed to be rather succesfull. We demonstrated the feasibility of a motivational approach through high adherence rates for LTC dwelling older people randomised in this clinical trial. Our target of 75 % compliance for the 8-weeks training project was by far attained. Furthermore, no individuals were considered non-compliant for the training. Thus, compliance with the exercise interventions and retesting was excellent. Compared with median rates for recruitment, attrition and adherence in falls prevention interventions in institutional settings for clinical trials [
82] we achieved better rates. However, we report on values after 8 training weeks. Nyman and Victor [
82] and Fuchs and colleagues [
64] report values that may be expected by 12 months. In future trials with LTC individuals the follow-up period for the assessment of adherence and attrition should, therefore, preferably be extended to a similar time frame to facilitate comparability with reference values.
Previous studies in elderly individuals have referred to the usefulness of WBV training on both muscle strength [
83‐
87] and balance [
88‐
91]. Playing certain types of Video Games had an effect on muscle strength [
92], balance [
93], and gait [
94]. However, few studies found results with similar high effect sizes as this study. The combination of SR-WBV and DVG might, therefore, be more effective in activating the sensorimotor system compared to published studies that investigated solely training using one of these approaches [
51,
83,
92‐
95]. However, future studies that compare both approaches against each other are needed to substantiate or refute this assumption. It is known that traditional strengthening improves muscle strength as a result of an improved neural drive and muscle hypertrophy [
96‐
98]. Gruber and Gollhofer [
72] postulated that sensorimotor training had a large influence on the neuromuscular system at the initiation of production of rate of force development and neuromuscular activation at the onset of voluntary actions. The motoneuron outputs induced by sensorimotor training comprise elevated central motor drive, motoneuron recruitment or firing frequency, alterations in synchronisation of motor unit firing, and reduced presynaptic inhibition [
72,
99]. However, the increase in IRFD after sensorimotor training is not associated with an increase in maximum voluntary contraction [
72]. As a sensorimotor training method, SR-WBV and DVG seems, therefore, to mainly affect the neural drive.
The results of the present study potentially have important functional consequences. Age-related degenerative processes, referred to as dynapenia, are considered a contributing factor to loss of independence in daily living [
20]. High RFD is important in various activities of daily life where a sudden strength capacity is required, and to counteract sudden perturbations, e.g., in postural control to avoid falls [
98,
100]. A typical contraction time involved in such movements is between 50 to 250 ms. In contrast, the time to reach maximum strength in most human muscles is over 300 ms, e.g., for knee extensors [
101]. On the basis of the previously described reasoning it seems plausible that IMVC did not significantly change during sensorimotor training. However, physical performance improved significantly. RFD is more closely related to physical performance than IMVC [
102,
103]. The result of this study is in accordance with Bottaro et al. [
104], who were able to find an increase in RFD in parallel with an improvement in physical performance.
This study presents a mean change after four weeks of about 2.7 points and after eight weeks of 4.2 points on the SPPB scale in the IG. After four weeks the SG shows a mean change of about −0.5 and after eight weeks a mean change −0.2 points on the SPPB scale. Changes of about 1 point on the SPPB scale are substantial [
105]. From a clinical standpoint, low SPPB point scores have a predictive value in activities in daily living [
69], loss of mobility [
106], admission to nursing facilities, disability [
66,
69], hospitalization [
107] and mortality [
108]. In addition, physical performance measures have been used to test the efficacy of preventive strategies [
109]. An improvement on the SPPB point scale through SR-WBV and DVG may reduce the risk of major mobility disability. Maintaining mobility is a central component in sustaining independence in daily living. Drey et al. [
105] described that muscle strength and muscle power during follow up interventions have been shown to be equally beneficial for increasing physical function in elderly individuals. Future studies should be designed with adequate follow up measures to further investigate and record the possible impact of SR-WBV and DVG on the activities of daily living.
An additional advantage of this current study over previous WBV or DVG investigations in the elderly is the use of the classification system defined by Zeyfang and Braun [
110]. Elderly individuals are not a homogeneous group. There are biologically elderly individuals who still feel young at heart, having a high physical fitness and performance level, and anticipating a few decades of life expectancy ahead of them. On the other spectrum frail elderly can be situated. Therefore, functional status of participating older individuals should be emphasized in training studies. To manage elderly individuals’ needs in consideration of diagnostic or treatment goals or maintenance of health, the framework “Go-Go, Slow-Go and No-Go” could be used. This classification was introduced by Zeyfang and Braun [
110] classifying older adults as “being an independent person” (Go-Go); “being a needy person with a slight handicap” (Slow-Go); and “being a person in need of care with severe functional limitation” (No-Go). The need for care may be defined as depending permanently on assistance (No-Go) or depending on support in everyday activities such as dressing, body care, eating, using the toilet, mobility, and planning the day (Slow-Go) [
111]. A systematic review indicated that older adults categorized in these groups react differently when provided with the same training stimuli [
38]. Our study reflects the need to consider the functional status of the included participants. Bautmans et al. [
88] included all residents in a nursing home within dependence categories “O” (do not need assistance), “A” (need assistance in two ADLs: washing and dressing) and “B” (require assistance in three ADLs) according to the scale of Katz et al. [
112]. When their participants are categorised with our classification it becomes apparent that only Go-Go and Slow-Go elderly were included. This finding is reflective of the observation that there are only few studies [
51,
83,
95,
113] that have focused separately on the Go-Go, Slow-Go and No-Go classification of older individuals.
There are some limitations in this study that should be mentioned. It was a single blind study. Studies where the examiner is not blinded might be at a higher risk of attrition [
114] or assessment bias [
115]. Future studies should, therefore, try to replicate our findings using a design where the examiner is blinded. No long-lasting effects follow-up measurements were obtained on the impact of the program on functional performance, strength or fall rates. Future studies should carry out such follow-up measurements to evaluate lasting effects. Furthermore, we used performance (SPPB) and impairment level (lower body muscle strength) based measures as proxies for PA [
116,
117]. Although these measures are correlated and randomised clinical trial intervention studies in older adults show that PA improves measures of physical performance [
109,
118] future studies should include quantified measures of PA instead of proxy measures.
Abbrevations
ADLs, activity of daily living; ANOVA, analyses of varianc; DVG, dance video game; ES, effect size; Fsub, Submaximal force; Hz, hertz; IG, intervention group; IMVC, isometric voluntary contraction; IRFD, isometric rate of force development; IRFDsub, submaximal IRFD values, Long-term care; LTC, MMSE, Mini-Mental Status Examination; ms, millisseconds; N, Newton; N/ms, Newton/milliseconds; RAI, Resident Assessment Instrument; RFD, rate of force development; SH, sham group; SPPB, Short Physival Performance Battery; SR-WBV, stochastic resonance whole-body vibration; WBV, whole-body vibration.