The relationship between trunk control and upper limb function in children with cerebral palsy

Abstract

BACKGROUND:

Trunk control ability greatly influences functional movement of the upper limbs.

PURPOSE:

Our primary aims were to assess trunk control ability, sway, and upper limb functions in children with cerebral palsy (CP), and to investigate the relationship between trunk control ability and upper limb function.

METHODS:

We included 15 children (8 boys and 7 girls) with CP. We used the Trunk Control Measurement Scale (TCMS) to evaluate trunk control ability and sway. We employed the Jebsen-Taylor Hand Function Test (JTHFT), the Quality of Upper Extremity Skills Test (QUEST), the Box and Blocks Test (BBT), and the ABILHAND-Kids questionnaire to explore upper limb function and arm movement acceleration. We calculated correlations between trunk control ability and parameters of upper limb function.

RESULTS:

TCMS scores correlated positively with the QUEST, BBT, and ABILHAND-Kids data, but negatively with the JTHFT findings. Anteroposterior acceleration correlated positively with JTHFT data, but negatively with QUEST, BBT, and ABILHAND-Kids data. Mediolateral acceleration correlated positively with the JTHFT outcomes, but negatively with those of QUEST, BBT, and ABILHAND-Kids.

CONCLUSIONS:

Upper limb function test data exhibited moderate to strong correlations with trunk control ability, as measured via the TCMS and triaxial accelerometry, in children with CP. Our results suggest that trunk control ability should be assessed when evaluating upper limb function in such children.

Keywords

Accelerometer cerebral palsy trunk control upper limb function

1. Introduction

Cerebral palsy (CP) is a group of non-progressive, permanent movement disorders caused by developmental delay of the fetal or infant brain [1]. CP is associated with motor deficits, including muscle weakness and poor coordination and posture [2]. Of these, deficient postural control is a major problem in children with CP [3]. Especially, thoracic kyphosis is excessively increased to compensate for the characteristic posterior pelvic tilt evident in individuals with CP [4]. Such motor difficulties interfere with goal-directed movement and the activities of daily living such as reaching [5].

Postural control is a subconscious process by which muscles work in harmony to maintain bodily alignment. Such control plays a key role in functional trunk and arm movements (such as reaching) required for normal daily living [6]. Abiko et al. [7] found that the multifidus muscle was activated earlier than the deltoid muscle during shoulder flexion in healthy subjects. Similarly, Okada et al. [8] found a significant correlation between core stability and functional performance.

Conventionally, the most commonly used tools for evaluating upper limb function are Jebsen Taylor hand function test (JTHFT) [18], Box and Blocks Test [22], and ABILHAND-Kids questionnaire [23]. Since the upper limb is connected to the trunk, it is significantly affected by the trunk function. However, most of the existing evaluation tools do not reflect the trunk control ability. In recent times, triaxial accelerometers have been used to analyze human dynamic movement; the devices are simple and inexpensive [9]. Moreover, accelerometers can be used in real-life clinical settings (thus not necessarily laboratories) because they are portable and responsive [10]. Some studies have used triaxial accelerometry to evaluate trunk sway [11] and functional reaching [12]. However, the interaction between trunk control ability and upper limb function in children with CP has received little attention. Therefore, our primary aim was to assess the correlations between the Trunk Control Measurement Scale (TCMS) score, trunk sway, and upper limb functions. Our secondary aim was to explore the relationship between trunk control ability and upper limb function in children with CP. We hypothesized that trunk control ability would affect upper limb function in such children. Our data will aid clinicians in assessing upper limb function in children with CP.

2. Methods

2.1 Subjects

The Institutional Review Board for Human Studies of Inje University approved this study (2017-01-012). All experimental protocols adhered to all relevant tenets of the Declaration of Helsinki. Prior to the study, we obtained informed consent from all parents or caregivers. We performed an a priori power analysis with G-Power version 3.1 software (University of Dusseldorf, Dusseldorf, Germany) to define an appropriate target sample size. Findings in 10 children could be predicted based on data from 5. We chose an effect size of 1.14, an 80% power, and an alpha error of 0.05. Our target sample size was 10. We included 15 children (8 boys and 7 girls) aged 7–13 (mean, 9.00 $\pm$ 1.13) years. The inclusion criteria were: (1) CP diagnosed by magnetic resonance imaging; (2) an ability to understand instructions given by investigators; (3) CP of level I–III, as scored using the Gross Motor Function Classification System; and (4) CP of grade 4–8, based on the House Functional Classification System [13]. The exclusion criteria were: (1) severe upper limb spasticity (MAS [modified Ashworth scale] $>$ 2), (2) orthopedic surgery on an upper limb within the previous 6 months, (3) the presence of sensory problems, and (4) a history of seizures that were or were not well controlled with therapy [14]. The demographic and general characteristics of all children are listed in Table 1.

Table 1
Clinical and demographic characteristics of the children

Children	Age	Gender	Height (cm)	Weight (kg)	Dignosis	HFCS ${}^{\rm a}$
1	9	B	132.7	33.7	Hemiplegia	5
2	10	B	128.2	23.8	Diplegia	4
3	7	B	133.6	35.7	Hemiplegia	5
4	10	B	127.5	25.2	Hemiplegia	6
5	10	G	125.8	29.5	Hemiplegia	6
6	9	G	131.6	35.2	Diplegia	5
7	7	G	119.3	35.4	Hemiplegia	7
8	7	G	125.0	28.0	Diplegia	5
9	10	B	145.9	45.9	Hemiplegia	6
10	9	G	131.5	31.3	Diplegia	6
11	9	G	125.4	23.3	Hemiplegia	6
12	10	G	128.7	25.3	Diplegia	5
13	9	B	135.3	30.0	Hemiplegia	6
14	9	B	129.6	25.6	Diplegia	4
15	10	B	137.8	36.6	Hemiplegia	6

HFCS ${}^{\rm a}$ : House Functional Classification System.

2.2 Outcomes

All subjects underwent a week-long familiarization process. Data collector and analyst were blinded so that the intent of the study was not reflected in the data analysis.

2.2.1 Tri-axial accelerometer

A triaxial accelerometer (Fitmeter; Fit.Life Inco., Suwon, Korea) was used to determine trunk sway during standing, and upper limb movement coordination during reaching, by calculating changes in acceleration. The accelerometer (35 $\times$ 35 $\times$ 13 mm, 13.7 g) consisted of a box, a sensor, and a battery. The sensitivity was $\pm$ 2 g and data were recorded at 128 Hz. Trunk acceleration has been used to evaluate motor performance associated with trunk sway [15] and upper limb coordination [16]. The sensor was fixed to the L3 spinous process when evaluating trunk sway and to the third metacarpal bone when measuring upper limb coordination. The $x$ axis represented the mediolateral (ML) direction, the $y$ axis represented the vertical (VT) direction, and $z$ axis represented the anteroposterior (AP) direction. Built-in software (Fitmeter Manager 2; Fit.Life Inco.) was used to calculate and display all data, which were exported as ASCII files prior to further analysis. The Fitmeter Manager software computed AP, ML, and VT acceleration as follows:

$\frac{dV}{dt}=\frac{dv}{dt}u_{t}+v(t)\frac{du_{t}}{dt}=\frac{dv}{dt}u_{t}+% \frac{v^{2}}{R}u_{n}$

where $u_{t}$ represents a change in direction, $v(t)$ represents a change in speed, $u_{n}$ is the normal unit vector, and $R$ is the instantaneous unit radius. We collected data under two different conditions. When measuring trunk sway, all children were required to stand barefoot, with the feet apart at shoulder width, and to look at a red point on a wall for 1 min. When assessing upper limb coordination, each child was asked to sit on an adjustable stool, and then engage in a reaching and touching task. The target was a small red ball (20 cm in diameter). In the trunk sway test, acceleration data were collected for 1 min, and those of the middle 30 s were evaluated. Upper limb acceleration data were gathered for 30 s in each of three successive trials; however, only data from typical 2-s periods were subjected to additional analysis. The intra-rater reliability of acceleration measurements was excellent ( $r=$ 0.92) [12].

2.2.2 Trunk control measurement scale (TCMS)

The TCMS was used to assess trunk control during sitting. The scale considers static balance, dynamic/sitting balance, and dynamic reaching. Previous reports found that reliability was excellent; the intra- and inter-rater intraclass correlation coefficients (ICCs) for evaluations of children with CP were 0.87–0.99 and 0.87–1.00, respectively [17]. Fifteen items are rated on 2–4-point ordinal scales; higher scores reflect better trunk control. All children were tested three times and the best score was used in data analysis. A break of about 10 s was allowed between each trial and a 1-min break was allowed between each test.

2.2.3 Jebsen Taylor hand function test (JTHFT)

The JTHFT was developed to assess hand function, and evaluates writing, card turning, grasping of small common objects, simulated feeding, playing of checkers, and lifting of large light and heavy objects. The time to complete all subtests is measured. On average, 15 min was required to complete all tests, which were presented identically to all children. All tests evaluated the non-dominant hand first, and then the dominant hand. The intra- and inter-rater reliability of JTHFT data, as characterized by ICC(1,1) values (0.516–0.814) and ICC(3,1) values (0.584–0.892), was acceptable [18]. The JTHFT subtest results exhibited strong internal correlations (Pearson’s correlation 0.140–0.854, $p<$ 0.01), and dynamometric data correlated well with JTHFT scores ( $p<$ 0.05) [18].

2.2.4 Quality of Upper Extremity Skills Test (QUEST)

The Quality of Upper Extremity Skills Test (QUEST) assesses upper extremity movements. Subitems include dissociated movement (of the shoulder, elbow, wrist, and fingers; a total of 64 items), grasping ability (of a cube, a cereal grain, and a crayon; a total of 24 items), weight-bearing ability (while prone and sitting; a total of 50 items), and protective extension (forward, sideways, and backward; a total of 36 items). Overall QUEST scores range from 0 to 100, with higher scores reflecting better upper extremity skills. All items are initially assessed as “yes”, “no”, or “not tested”, and then scored using a defined formula. The assessment requires 30–45 min. All tests were performed as recommended in the relevant manual [19]. The intra-rater reliability of QUEST data from an evaluation of children with CP was moderate to strong (ICC $=$ 0.84–0.90) and the inter-rater reliability was strong (ICC $=$ 0.84–0.94) [20]. In addition, a strong correlation was evident between Melbourne Assessment and QUEST data (Pearson’s correlation coefficient 0.83, $p<$ 0.001) [21].

2.2.5 Box and Blocks Test (BBT)

The BBT is used widely to evaluate manual and upper limb skills. The number of blocks moved during 60 s is used to assess the functional ability of the hand and arm. First, the child sits on a chair facing two test boxes placed on a table at a standard height, one of which contains 150 colored 2.5-cm wooden cubes. All blocks are in one box. Before the test, each child is allowed 15 s for familiarization. When the 60-s test starts, the child is asked to transfer as many blocks as possible to the other box using the more-affected hand. After testing, the transferred blocks are counted. The test is performed twice and an average is calculated. The inter- and intra-rater reliability of the BBT is excellent (ICCs $=$ 0.99 and 0.96, respectively). Furthermore, a strong correlation was apparent between the Fugl-Meyer motor test and BBT results (Spearman’s $r=$ 0.92) [22].

2.2.6 ABILHAND-Kids questionnaire

The ABILHAND-Kids questionnaire is used to measure bimanual ability in children with CP. It consists of 21 items exploring daily community activities; all are initially graded as impossible, difficult, or easy. These raw scores are then converted into a linear measure using the Rasch model. The questionnaire is completed by caregivers. In an evaluation of children with CP, the questionnaire showed a high degree of reliability ( $r=$ 0.94) and good reproducibility ( $r=$ 0.91) [23].

2.3 Statistical analysis

All results are presented as means with standard deviations. We calculated Pearson correlation coefficients reflecting linear correlations between trunk control abilities and functional reaches of the upper limbs. PASW statistical software (ver. 20; Norusis/SPSS Inc., Chicago, IL, USA) was used to this end. Two-tailed $p$ values $<$ 0.05 were considered to reflect statistical significance.

3. Results

We found significant correlations between trunk control ability and upper limb function (Table 2). The TCMS scores correlated positively with the QUEST, BBT, and ABILHAND-Kids scores (all $p<$ 0.05), but negatively with the JTHFT scores ( $p<$ 0.05). AP acceleration was correlated positively with the JTHFT score, but negatively with the QUEST, BBT, and ABILHAND-Kids scores. The TCMS score was associated significantly with the JTHFT, QUEST, and BBT scores ( $p<$ 0.05), but not with the ABILHAND-Kids score ( $p>$ 0.05). ML acceleration was correlated positively with the JTHFT score, but negatively with the QUEST, BBT, and ABILHAND-Kids scores (all $p<$ 0.05).

Table 2
Correlation between trunk control ability and upper limb functions

	TCMS ${}^{\rm a}$		AP ${}^{\rm b}$ acceleration		ML ${}^{\rm c}$ acceleration
	$r$	$p$	$r$	$p$	$r$	$p$
JTHFT ${}^{\rm d}$	$-$ 0.855 ${}^{*}$	0.000	0.705 ${}^{*}$	0.003	0.784 ${}^{*}$	0.001
QUEST ${}^{\rm e}$	0.622 ${}^{*}$	0.013	$-$ 0.521 ${}^{*}$	0.046	$-$ 0.720 ${}^{*}$	0.002
BBT ${}^{\rm f}$	0.647 ${}^{*}$	0.009	$-$ 0.627 ${}^{*}$	0.012	$-$ 0.741 ${}^{*}$	0.002
ABILHAND-Kids	0.700 ${}^{*}$	0.004	$-$ 0.512	0.051	$-$ 0.531 ${}^{*}$	0.042
ML acceleration	$-$ 0.537 ${}^{*}$	0.039	0.721 ${}^{*}$	0.002	0.685 ${}^{*}$	0.005
VT ${}^{\rm h}$ acceleration	$-$ 0.399	0.140	0.675 ${}^{*}$	0.006	0.584 ${}^{*}$	0.022

TCMS ${}^{\rm a}$ : Trunk Control Measurement Scale; AP ${}^{\rm b}$ : anterio-posterior; ML ${}^{\rm c}$ : medio-lateral; JTHFT ${}^{\rm d}$ : Jebsen Taylor Hand Function Test; QUEST ${}^{\rm e}$ : Quality of Upper Extremity Skills Test; BBT ${}^{\rm f}$ : Box and Blocks Test; VT ${}^{\rm h}$ : vertical.

4. Discussion

We explored the relationship between trunk control ability and upper limb function. We assessed trunk control ability by calculating TCMS scores via analysis of triaxial accelerometric data. We used the JTHFT, QUEST, BBT, and ABILHAND-Kids measures to explore upper limb function in children with CP. To our knowledge, this clinical study is the first to calculate correlations between trunk control ability and upper limb function measured using the JTHFT, QUEST, BBT, and ABILHAND-Kids instruments. The TCMS and trunk sway scores correlated significantly with the JTHFT, QUEST, BBT, and ABILHAND-Kids scores.

Several significantly positive (TCMS with QUEST, BBT, and ABILHAND-Kids) and negative (TCMS with JTHFT) correlations were apparent between trunk control and upper limb functional variables. These correlations exist because higher QUEST, BBT, and ABILHAND-Kids scores indicate that functionality is better; the reverse is true of the JTHFT scores. In addition, the strength of the correlations decreased in the order JTHFT, ABILHAND-Kids, BBT, and QUEST. Thus, the extent of trunk control significantly influenced upper limb function. There were no previous studies that could be compared with our results. Similarly, Woodbury et al. [24] investigated the effects of trunk training on upper extremity reach and function in patients with chronic stroke sequelae. They found that trunk training improved arm reach trajectories, shoulder flexion, and the elbow extension range of motion [24]. Cherng et al. [25] compared the reaching ability between children with CP and healthy children. They found that the normalized ground reaction force of children with CP (31–53%) was significantly smaller compare to the healthy children (47–61%) during reaching [25].

AP trunk acceleration correlated positively with the JTHFT and negatively with the QUEST, BBT, and ABILHAND-Kids scores, in the order JTHFT, BBT, QUEST, and ABILHAND-Kids. ML trunk acceleration correlated positively with the JTHFT and negatively with the QUEST, BBT, and ABILHAND-Kids scores, in the order JTHFT, BBT, QUEST, and ABILHAND-Kids. These correlational relationships exist since high AP and ML acceleration indicates high-level trunk sway, associated with poor trunk control ability. Besides, higher QUEST, BBT, and ABILHAND-Kids scores suggest that upper limb functionality is better, whereas, higher JTHFT scores indicate that upper limb functionality is poor. Thus, our data suggests that the higher the AP and ML trunk accelerations sway, the poorer the upper limb function. Our data supports an earlier finding that that core stability increases with functional movement and performance [8]. Sahinoglu and Coskun [4] found that good postural alignment facilitated by adjustable seating significantly improved arm control ability, compared with that afforded by traditional postural alignment.

Together, our results show that that (in order) the JTHFT, BBT, QUEST, and ABILHAND-Kids scores correlated with the TCMS score and associated trunk sway in children with CP. Although a strong correlation between trunk control ability and upper limb functionality was evident, trunk control ability is not usually evaluated when assessing upper limb function in children with CP. We thus suggest that clinicians should evaluate trunk sway, rather than assessing upper extremity function only, when exploring upper limb function in children with CP. As upper limb function measures, such as the JTHFT score, correlate strongly with trunk sway, such data are useful to clinicians.

Our study had two major limitations that should be considered when planning future research. First, because we focused on children with CP, the sample was small. Larger samples are needed. In addition, further studies are needed to compare trunk control ability between children with hemiplegic CP and diplegic CP. Second, we investigated the relationships between the TCMS score and only trunk sway and upper limb function. Future studies should include other trunk tests. Finally, we measured trunk sway only in standing position. Future studies should reflect trunk sway in various positions.

5. Conclusion

Upper limb functionality exhibited a moderate to strong correlation with trunk sway. Clinicians should consider the extent of trunk control when assessing upper limb function in children with CP. In particular, we recommend that trunk sway should be measured via simple triaxial accelerometry when clinically evaluating upper limb function.

Footnotes

Conflict of interest

None to report.

References

Rosenbaum

, et al., A report: the definition and classification of cerebral palsy April 2006. Dev Med Child Neurol Suppl, 2007; 109: 8-14.

Bax

, et al., Proposed definition and classification of cerebral palsy, April 2005, Dev Med Child Neurol, 2005; 47(8): 571-576.

van der Heide

, and Hadders-Algra

, Postural muscle dyscoordination in children with cerebral palsy. Neural Plast, 2005; 12(2-3): 197-203.

Sahinoglu

Coskun

, and Bek

, Effects of different seating equipment on postural control and upper extremity function in children with cerebral palsy. Prosthet Orthot Int, 2017; 41(1): 85-94.

Steenbergen

, and Gordon

, Activity limitation in hemiplegic cerebral palsy: evidence for disorders in motor planning. Dev Med Child Neurol, 2006; 48(9): 780-783.

Ryerson

, et al., Altered trunk position sense and its relation to balance functions in people post-stroke. J Neurol Phys Ther, 2008; 32(1): 14-20.

Abiko

, et al., Difference in the electromyographic onset of the deep and superficial multifidus during shoulder movement while standing. PLoS One, 2015; 10(4): e0122303.

Okada

Huxel

, and Nesser

, Relationship between core stability, functional movement, and performance. J Strength Cond Res, 2011; 25(1): 252-261.

Moe-Nilssen

, and Helbostad

, Trunk accelerometry as a measure of balance control during quiet standing. Gait Posture, 2002; 16(1): 60-68.

10.

Godfrey

, et al., Direct measurement of human movement by accelerometry. Med Eng Phys, 2008; 30(10): 1364-1386.

11.

Curtis

, et al., Measuring postural sway in sitting: a new segmental approach. J Mot Behav, 2015; 47(5): 427-435.

12.

Yoo

, et al., Augmented effects of EMG biofeedback interfaced with virtual reality on neuromuscular control and movement coordination during reaching in children with cerebral palsy. NeuroRehabilitation, 2017; 40(2): 175-185.

13.

Rosenbaum

, et al., Development of the Gross Motor Function Classification System for cerebral palsy. Dev Med Child Neurol, 2008; 50(4): 249-253.

14.

Lazzari

, et al., Effect of transcranial direct current stimulation combined with virtual reality training on balance in children with cerebral palsy: A randomized, controlled, double-blind, clinical trial. J Mot Behav, 2017; 49(3): 329-336.

15.

Mayagoitia

, et al., Standing balance evaluation using a triaxial accelerometer. Gait Posture, 2002; 16(1): 55-59.

16.

Michaelsen

, et al., Using an accelerometer for analyzing a reach-to-grasp movement after stroke. Motriz. Revista de Educacao Fisica, 2013; 19(4): 746-752.

17.

Heyrman

, et al., A clinical tool to measure trunk control in children with cerebral palsy: the Trunk Control Measurement Scale. Res Dev Disabil, 2011; 32(6): 2624-2635.

18.

Culicchia

, et al., Cross-cultural adaptation and validation of the Jebsen-Taylor Hand Function Test in an Italian population. Rehabil Res Pract. 2016; 2016: 897-917.

19.

DeMatteo

, QUEST: quality of upper extremity skills test. 1992: DeMatteo.

20.

Haga

, et al., Test-retest and inter- and intrareliability of the quality of the upper-extremity skills test in preschool-age children with cerebral palsy. Arch Phys Med Rehabil, 2007; 88(12): 1686-1689.

21.

Klingels

, et al., Comparison of the Melbourne Assessment of unilateral upper limb function and the Quality of Upper Extremity Skills Test in hemiplegic CP. Dev Med Child Neurol, 2008; 50(12): 904-909.

22.

Platz

, et al., Reliability and validity of arm function assessment with standardized guidelines for the Fugl-Meyer Test, Action Research Arm Test and Box and Block Test: a multicentre study. Clin Rehabil, 2005; 19(4): 404-411.

23.

Arnould

, et al., ABILHAND-Kids: a measure of manual ability in children with cerebral palsy. Neurology, 2004; 63(6): 1045-1052.

24.

Woodbury

, et al., Effects of trunk restraint combined with intensive task practice on poststroke upper extremity reach and function: a pilot study. Neurorehabil Neural Repair, 2009; 23(1): 78-91.

25.

Cherng

, et al., Effect of seat surface inclination on postural stability and forward reaching efficiency in children with spastic cerebral palsy. Res Dev Disabil, 2009; 30(6): 1420-1427.