Research in Developmental Disabilities 35 (2014) 110–116

Contents lists available at ScienceDirect

Research in Developmental Disabilities

Development and validation of the computerized bilateral motor coordination test Chin-Kai Lin a,*, Huey-Min Wu b a

Program of Early Intervention, Department of Early Childhood Education, National Taichung University of Education, 140 Min-Shen Road, Taichung 40306, Taiwan b Research Center for Testing and Assessment, National Academy for Education Research, No. 2, Sanshu Road, Sanxia District, New Taipei 237, Taiwan

A R T I C L E I N F O

A B S T R A C T

Article history: Received 30 August 2013 Received in revised form 22 October 2013 Accepted 22 October 2013 Available online 16 November 2013

The purpose of this study was to explore the validity of computerized scaling of bilateral, motor coordination in children 4–6 years of age. There were 623 children with an average age of 5, years and 2 months (standard deviation = 6 months) that participated. The 290 girls (46.5%) and 333, boys (53.5%) were from a purposive sample taken from public and private kindergartens in Taiwan. The computerized bilateral motor coordination test included two subtests, bilateral coordination, movements and projected actions. The motion analysis, with mark position and contour motion, was, used to collect important variables from the subtests. Using the judgments of the experts as the, criterion standards, the accuracy, sensitivity, and specificity of the tool were calculated to evaluate the, validity of the computerized bilateral motor coordination test. The accuracy, sensitivity, and, specificity of the bilateral coordination movement subtests were on average 83.9%, 86.4%, and 83.1%, respectively. The accuracy, sensitivity, and specificity of the projected action subtests were on average, 90.5%, 88.1%, and 90.4%, respectively. The computerized bilateral motor coordination tests showed, an average accuracy of 86.3%, a sensitivity of 87.0%, and a specificity of 85.8%. The computerized, bilateral motor coordination test could be a valuable tool when used to identify problems of bilateral, motor coordination and in permitting early intervention to remedy these problems. ß 2013 Elsevier Ltd. All rights reserved.

Keywords: Motor coordination Validity Bilateral motor integration Projected action

1. Introduction Motor coordination is defined as the body’s activation of the proper muscles required for purposeful, controlled, accurate and quick movements (Desrosiers, Rochette, & Corriveau, 2005). Bilateral coordination is defined as the ability to use both sides of the body in a skillful and integrated way (Magalhaes, Koomar, & Cermak, 1989). Bundy, Lane, and Murray, believing that bilateral coordination also involves repeated and continuous sequences of actions and projected actions, introduced the concept of bilateral integration sequencing (Bundy, Lane, & Murray, 2002). Some developmental disorders may demonstrate motor coordination impairments, such as autism (Fournier, Hass, Naik, Lodha, & Cauraugh, 2010), ADHD (Piek, Pitcher, & Hay, 1999), developmental coordination disorder (DCD) (Huh, Williams, & Burke, 1998), developmental delay or learning disability (Cermak, Trimble, Coryell, & Drake, 1990). The children with motor coordination impairment are usually described as clumsy. Lack of bilateral coordination may result in low performance in

* Corresponding author. Tel.: +886 422015451; fax: +886 422183380. E-mail addresses: [email protected], [email protected] (C.-K. Lin). 0891-4222/$ – see front matter ß 2013 Elsevier Ltd. All rights reserved. http://dx.doi.org/10.1016/j.ridd.2013.10.026

C.-K. Lin, H.-M. Wu / Research in Developmental Disabilities 35 (2014) 110–116

111

basic motor skills (e.g., balance, ball playing skills or dexterity) (Poulsen, Johnson, & Ziviani, 2011), activities of daily life, academic performance (Cardoso & Magalhaes, 2009), voluntary movements, sports or rhythmic activities. When such children move awkwardly in relation to their peers, they may also suffer from low self-esteem (Cocks, Barton, & Donelly, 2009). For children, bilateral coordination is an extremely important element of their development. There are four types of bilateral movements: symmetrical bilateral, asymmetrical bilateral, alternating bilateral and skilled bilateral. Symmetrical bilateral movements are synchronized movements performed by two sides of the body or both hands. In such movements, the two hands must move the same distance and in the same direction, as in clapping (Huh et al., 1998). Two examples of children’s games that involve bilateral symmetrical movements are jumping rope and swinging. A child on a swing has to flex and extend both arms at the same time. Asymmetrical bilateral movements are asynchronous movements by two sides of the body in different directions or at different speeds (Huh et al., 1998). Examples of such movements include using a hula hoop, peeling an apple and cutting paper. Alternating bilateral movements are movements that alternate between the two sides of the body. An example of such a movement is playing a drum set. Finally, skilled bilateral movements are action sequences that are dynamic, fast, continuous and projected. These movements require anticipation of time and space. Ball sports are examples of skilled bilateral movements. There are three basic axial planes in human movement, including sagittal plan, frontal plane, and transversal plane (Cael, 2010). The sagittal plane is from the front to the rear and divides the body into left and right halves. The frontal plane is from the right side to the left side or from the left side to the right side and divides the body into the anterior and posterior. The transversal plane divides the body into superior and inferior parts. Examples of movements in sagittal plan, frontal plane, and transversal plane are walking forward and backward, jumping to the left and right sides, and jumping up and down, respectively. Most of the skilled bilateral movements are complex movements across three axial planes, such as dancing, or gymnastics. Tools used to evaluate coordination mainly consider continuity, rhythm, speed, quality of movement, accuracy and movement planning (Desrosiers et al., 2005). Items traditionally used to evaluate bilateral movement include jumping in place, Jumping Jacks (symmetrical stride jumps), throwing, kicking and catching a ball (Bruininks, 2005; Henderson & Sugden, 1992). The most commonly used tools in Taiwan to evaluate motor coordination are the movement assessment battery for children (M-ABC) (Watter, 2006) and the Bruininks-Oseretsky test of motor proficiency (BOTMP) (Bruininks, 2005). M-ABC and BOTMP can be used to diagnose children with DCD, a sensory integration dysfunction, or a high level of clumsiness. The sensory integration and praxis test (SIPT) (Ayres, 1989) is designed to evaluate one’s ability to perform bilateral integration and sequencing via two of its 17 sub-tests: bilateral motor coordination and sequencing praxis. SIPT is seldom administered in the health care and educational systems in Taiwan, as SIPT is expensive and few practitioners are SIPT-certified. In past studies, motor coordination scores were usually measured by observing the time required to complete an action or the number of times the subject can complete an action. As a result, errors may occur when the researcher’s view is obscured or when information is lost (e.g., error in counting). Advanced technology has allowed the use of image analysis software to assess movement. If a subject can be observed at different angles, visual blocking can be eliminated. Image analysis can also increase the accuracy of counting and obtain more information, such as height and angle. Using the computer to analyze the complex information also results in a fast, accurate diagnosis. Currently, there are no standardized tests to evaluate bilateral coordination of children in Taiwan, nor is there normative data by which to screen children’s bilateral motor function. This study sought to develop a set of computerized tools to evaluate children’s bilateral motor function. The purpose of this study is to explore the validity of the computerized scaling of bilateral motor coordination in children aged 4–6 years. This study expects to develop the computerized scaling system of software that could assist clinical clinicians in automatically identifying subjects with motor function deficiencies. 2. Methods 2.1. Participants and procedures The study was conducted from August 2010 to July 2011. In this study, 623 children with an average age of 5 years and 2 months (standard deviation = 6 months) participated. The 290 girls (46.5%) and 333 boys (53.5%) were from a purposive sample taken from public and private kindergartens in Taiwan. There were 201 4-year-olds (99 girls and 102 boys), 226 fiveyear-olds (106 girls and 120 boys) and 196 six-year-olds (85 girls and 111 boys). None of the children had any history of neural or orthopedic illness. The demographic information is listed in Table 1.

Table 1 Sample by age and sex. Age (years)

Boys

Girls

Total

4 5 6 Total

102 120 111 333

99 106 85 290

201 226 196 623

(50.7%) (53.1%) (56.6%) (53.5%)

(49.3%) (46.9%) (43.4%) (46.5%)

112

C.-K. Lin, H.-M. Wu / Research in Developmental Disabilities 35 (2014) 110–116

The researchers went to each kindergarten to explain the purpose of the study. Then, consent forms were sent to those parents willing to participate. After the parents signed and returned the forms, researchers went to the kindergarten to set up the test equipment and collect data. During testing, two children that are selected at random from among the total number of participants in each classroom, enter the filming studio at the same time. One of the children is led to stand at the pre-marked spot at the center of the studio. The researcher then provides instructions for the child to follow and demonstrates the movements while the other child observes at the side. This child who observes is told beforehand to not make any movements or noises to disturb the subjects during the test. When the first child has finished, they trade places so that the observer becomes the subject. To avoid fatigue, the subjects are given a 2–3 min break between the bilateral coordination tests and the anticipatory coordination tests. 2.2. The items of the computerized bilateral motor coordination test There are two subtests in the computerized bilateral motor coordination test, including bilateral coordination (7 items) and projected actions (2 items). The bilateral coordination items are: Jumping Two Hand Coordination, Hand and Opposite Feet Coordination, Two-Hand and One Foot Coordination, Forward and Backward Stepping, Alternating Foot Jump, Jumping Table 2 The computerized bilateral motor coordination test for arm–leg coordination. Test Item

Instructions for movement

Computer scoring variable

Two Hand Coordination

Right arm moves up and down while the left arm moves to the left and right with elbow held flat, followed by the left arm moving up and down while the right arm moves to the left and right with elbow held flat

Hand and Opposite Feet Coordination

Right arm raised forward 90 degrees, while the left foot is raised to the side, followed by the opposite side motion

Two-Hand and One Foot Coordination

Two arms raised to the right while the left foot is raised to the front by 45 degrees, followed by the two arms raised to the left while the right foot is raised to the front by 45 degrees

Forward and Backward Stepping

Right foot steps in front while left foot lifts up slightly. Right foot steps back while left foot lifts up when right foot touches the ground. Do the same thing with opposite foot

Alternating Foot Jump

Right leg jump forward and with the left leg extend back

Jumping Jacks without Hand Motion

Both feet extend out, jump, then both feet back in

Jumping Jacks

First jump up, spreading feet apart, and raising arms above the head to clap hands. Then jump up again, bringing feet back together, and moving arms back down to the sides

Sandbag Catching

Throw sandbag upwards with right hand, and then catch it with both hands. Change to left hand after 10 times

Stepping on Balls

Researcher rolls a ball toward the subject. Subject steps on it with right foot. Switch to the left after ten times

(1) (2) (3) (4) (5) (1) (2) (3) (4) (5) (6) (1) (2) (3) (4) (5) (6) (7) (1) (2) (3) (4) (5) (6) (1) (2) (3) (4) (5) (6) (1) (2) (3) (4) (5) (6) (1) (2) (3) (4) (5) (6) (7) (1) (2) (3) (4) (1)

Angle the neck bends to the side Angle the trunk bends to the side Distance variance of vertical motion Period of horizontal motion Number of completions Angle the neck bends to the side Angle the trunk bends to the side Standardized height of arm raised Standardized height of foot raised Period of arm and foot motion Number of completions Angle the neck bends to the side Angle the trunk bends to the side Standardized height of arm raised to one side Standardized height of arm raised to the other side Standardized height of foot raised Period of arm and foot movements Number of completions Angle the neck bends to the side Angle the trunk bends to the side Standardized distance between two feet Period of foot movement Angle that the knee bends Number of completions Angle the neck bends to the side Angle the trunk bends to the side Standardized distance between two feet Angle that the knee bends Period of foot movement Number of completions Angle the neck bends to the side Angle the trunk bends to the side Standardized distance of the feet Angle that the knee bends Period of foot movement Number of completions Angle the neck bends to the side Angle the trunk bends to the side Standardized distance between the two hands Standardized distance between the two feet Angle that the knee bends Period of arm and feet movement Number of completions Angle the neck bends to the side Angle the trunk bends to the side Standardized height of sandbag throw Number of catches Number of completions

Note: The subjects must stand upright, stay in place, start each movement with the right leg and arm, and perform each movement for 20 s.

C.-K. Lin, H.-M. Wu / Research in Developmental Disabilities 35 (2014) 110–116

113

Jacks without Hand Motion, and Jumping Jacks. The projected actions are: Sandbag Catching, and Stepping on Balls (see Table 2). The rationale for two subtests is based on the concept of bilateral motor coordination (Bundy et al., 2002). The previous assessment tools (Bruininks, 2005; Magalhaes et al., 1989; Watter, 2006) are for reference in designing test items. The test items comprise the components of symmetrical, asymmetrical, alternating, sequential or skilled bilateral movements. The axial movements in this study are the action patterns of sagittal, frontal, or transversal plane. The movements in the sagittal plane include Forward and Backward Stepping, with the right leg jumping forward and the left leg extending back (Alternating Foot Jump). The movements in the frontal plane include Jumping Jacks without Hand Motion, Jumping Jacks, and Two-Hand and One Foot Coordination (Table 2). The movements in the transverse plane include various jumping movements and Stepping on Balls. Some complex actions contain two or three axial planes, such as Two Hand Coordination, Hand and Opposite Feet Coordination, and Two-Hand and One Foot Coordination. 2.3. Materials 2.3.1. Apparatus The testing site is an L-shaped film studio 3 m long, 3 m wide and 2.5 m tall. The studio is large enough to accommodate one subject performing movements inside the space, and three cameras to record the movement. The three cameras are set up at the front, side and top of the studio. Filming subjects from three angles eliminates errors caused by obstructions. 2.3.2. Motion analysis procedures This study captures the video through visual surveillance at 30 frames per second. Every movement was filmed for 20 s at a resolution of 640  480 pixels with a 32-bit color level. The subject’s movements are captured from three views (front, side and top). Through motion analysis (Hu, Tan, Wang, & Maybank, 2004), information such as marker position, silhouette and contour is obtained via Open Source Computer Vision Library (Open CV software provided by opencv.org). The scoring model is developed by statistical analysis of the identified movements. The motion analysis process is described below. 2.3.2.1. Mark position motion analysis. 1. Background Color: each subject wears a specially designed body suit, and each important body joint is marked with a different color (red, blue, green and yellow) as shown in Figs. 1 and 2. This study utilizes the adaptive threshold background model (Gonzalez, Woods, & Eddins, 2009) to mark the colors. 2. Filter operation: during image analysis, the colored spots may be distorted by shadows and the contours may appear to be broken. In this study, we repair the broken contours by using the closing and opening technique in morphology in order to calculate the center of mass of the colored marks (Gonzalez et al., 2009). 3. Recording of position: the coordinates of each mark are recorded to present its position at a specific point in time. 4. Tracking: all marked spots on the same part of the body suit are the same color. As a result, two or three colored spots are tracked at the same time. Each image is compared to the previous one for motion tracking. Tracking the center of mass for each spot allows us to put all X and Y values on a timeline. By calculating the changes in X and Y, we can determine how the subject moves in a 20-s period. Fig. 1 illustrates this process. During the two-hand coordination tests, the front camera records the subject’s right hand movements (green). 2.3.2.2. Contour motion analysis. 1. The filming studio has a white background and is designed to fit one subject at a time. By using the RGB value (255, 255, 255) of the film, it is easy to differentiate between the background and the subject. Since the subjects are the largest part of the image, keeping the subject in the image eliminates visual noise. The confined size of the studio simplifies this process.

Fig. 1. Two hand coordination motion analysis. (For interpretation of the references to color in text, the reader is referred to the web version of this article.)

114

C.-K. Lin, H.-M. Wu / Research in Developmental Disabilities 35 (2014) 110–116

Fig. 2. Contour motion analysis of Jumping Jacks without Hand Motion. (For interpretation of the references to color in text, the reader is referred to the web version of this article.)

2. The lighting may obscure some of the motion points during movement of the subject. However, using the imaging software, we can reconstruct the path of movement and recover the data points. 3. By recording the change in contour area, we can obtain the changes in height and width of the colored spots along an axis over time. Plotted on a graph, we are able to track the subject’s movement through space over time. Fig. 2 provides an example of this process. The frontal camera records the subject’s Jumping Jacks without Hand Motion and the resulting data is shown in a graph (Fig. 2) of his foot movement. The researchers collected important variables from 9 movements by using the motion analysis process above. The definition of each performance measurement and the variables collected are provided in Table 2. 2.4. Statistics This study uses the maximum likelihood classification system. By using cross-validation with a k-fold (k = 5), the samples were randomly assigned to five groups. One of these groups is picked as the test data, while the other four are used as training data (Kuncheva, 2004). By repeating this process five times until every sample has been used as test data once, we can calculate the accuracy, identification accuracy, sensitivity and specificity of the test. All statistical analyses were performed using MATLAB (MathWorks, Natick, MA). 2.5. Evaluation criteria The subject’s performances were ranked based on the image analysis and interviews conducted by experts. In this study, the computerized tools also ranked each subject’s performance in bilateral coordination. Based on the rankings of both experts and the computer tool, the sensitivity, specificity and accuracy of the tool were obtained to evaluate the validity of the computerized bilateral motor coordination test. Accuracy was obtained by dividing the number of subjects diagnosed with the same ranking by both the experts and the computerized tool (i.e., either both with or both without) by the total number of subjects. Sensitivity was obtained by dividing the number of subjects diagnosed by the experts as having bilateral integration sequencing impairments by the number diagnosed by the computerized tools as having bilateral integration sequencing impairments. Specificity was obtained by dividing the number of subjects diagnosed by the experts as being free of bilateral integration sequencing impairments by the number of those diagnosed by the computerized tool as being free of bilateral integration sequencing impairments. 3. Results Table 3 shows that, in all 9 of the movement coordination tests, the accuracy of the computerized tool exceeded 80%. This indicates that the results obtained by computerized tools are consistent with the opinions of experts. In terms of their correlation with expert opinion, the computerized tools developed in this study have excellent validity. When evaluating bilateral coordination, the accuracy of the tools is 80.5–88.9%. Forward and Backward Stepping had the highest accuracy (88.9%) while Two Hand Coordination had the lowest (80.5%). Sensitivity was 74.8–94.5%, with Forward

C.-K. Lin, H.-M. Wu / Research in Developmental Disabilities 35 (2014) 110–116

115

Table 3 Performance indices of the computerized bilateral integration motor test in children 4–6 years. Test item

Accuracy (%)

Sensitivity (%)

Specificity (%)

Bilateral coordination

Two Hand Coordination Two-Hand and One Foot Coordination Hand and Opposite Feet Coordination Forward and Backward Stepping Alternating Foot Jump Jumping Jacks without Hand Motion Jumping Jacks

80.5 85.4 81.7 88.9 84.6 85.1 81.4

89.6 74.8 83.8 94.5 86.1 91.5 84.5

76.1 87.5 80.9 88.6 84.3 84.5 80.0

Projected actions

Left Hand Sandbag Catching Right Hand Sandbag Catching Left Foot Stepping on Balls Right Foot Stepping on Balls

89.1 93.2 89.3 90.2

90.9 93.5 75 92.9

88.5 93.2 89.8 90.1

and Backward Stepping, with Jumping Jacks without Hand Motion having at least 90% sensitivity. Two-Hand and One Foot Coordination, movements which require bilateral coordination specificity, showed the lowest sensitivity at 74.8%. The possible reason for this lowest sensitivity will be mentioned in the discussion section. Specificity was 76.1–88.6%, with TwoHand and One Foot Coordination, with Forward and Backward Stepping having at least 85% specificity. In terms of projected actions, Sandbag Catching and Stepping on Balls are related to the subject’s handedness, so we counted the left hand, right hand, left foot and right foot separately. All four showed an accuracy of over 89%, a sensitivity of 75–93.5%, and 88.5–93.2% specificity (Table 3). Subjects using the right hand to throw the sandbags all showed a higher accuracy than those using the left hand, due to the fact that most subjects are right-handed. As a result, impairments of the right hand can be more easily identified. As for stepping on balls, handedness seems to have the same effect, since subjects using the right foot to step on a ball showed a higher accuracy than those using the left foot. 4. Discussion The purpose of this study is to determine the validity of using the computerized bilateral motor coordination test to identify bilateral coordination in children aged 4–6 years. The bilateral motor integration screening accuracy was found to be between 80.5% and 93.2% (Table 3). Therefore, the computerized bilateral motor coordination test developed in this study can be deemed a valid instrument to identify bilateral coordination or lack of coordination in most children, on a par with expert opinion. The study also indicates that the Two-Hand and One Foot Coordination test item is a relatively less important variable due to its low sensitivity at 74.8%. One possible reason for this score is that experts can directly assess ipsilateral and contralateral hand–foot coordination, while the computerized tool can only measure the angle of the arm, the angle of the foot, the standardized height and the movement periods. This inability to measure all pertinent factors may result in the low sensitivity. For the Left Foot Stepping on Balls test item, the sensitivity is low at 75%. The experts considered the ability to control the stepping on ball test, such as slow foot placement on the ball, compared to the computerized bilateral motor coordination test, which does not detect physical strength that the participant used. There is only one test item, Two Hand Coordination, which has a low specificity, at 76.1%. The possible reason for this is that experts do not consider the distance of vertical motion on shoulder flexion in the performance ratings, while the computerized bilateral motor coordination test does. The computerized tool developed in this study shows excellent validity and is a clear improvement over currently available tools such as the M-ABC. Rodger et al. (2007) doubted the sensitivity of M-ABC when they found that only 58% of children diagnosed with motor coordination impairment fit M-ABC’s criteria. Rodger et al. believed that M-ABC is unable to take into account all the variances of motor performance for DCD (Rodger et al., 2007). M-ABC does not include coordination in the sagittal plane for children less than 6 years of age. Sagittal plane movements include motions to the left or right, like a sideways jump. High, Gough, Pennington, and Wright (2000) believed that the M-ABC does not include such abilities as motor planning, bilateral integration or sequencing (High et al., 2000). M-ABC also lacks evaluation of asymmetrical alternating movements or movements that require coordination between the arms, legs or body. The SIPT does not take into account such elements as quick movements or projected action sequences, such as coordination while jumping. Bundy et al. indicated that the SIPT requires additional observation of children catching a bouncing ball, hopping or jumping in series of circles, skipping, doing the Jumping Jacks and stepping over a moving object (Bundy et al., 2002; Magalhaes et al., 1989). This tool improves on the shortcomings of M-ABC and SIPT by including symmetrical, asymmetrical alternating and skilled movements in its computerized evaluations. To evaluate bilateral coordination, BOTMP provides a complete set of tests. BOTMP focuses on quantity by recording the number of correct Jumping Jacks, jumping in place (same side synchronized), and jumping in place (opposite side synchronized). The scores are kept by recording the number of completions and the quality of the movements in this study. The angles, standardized height, period and standardized distance of the joint movements are all recorded. Compared with M-ABC, SIPT and BOTMP, all of which use norm-referenced methods to evaluate bilateral coordination, this study utilizes cross-validation with expert judgment for screening and diagnosis.

116

C.-K. Lin, H.-M. Wu / Research in Developmental Disabilities 35 (2014) 110–116

In order to obtain accurate data, the computerized tool requires that participants wear a specially designed body suit. The suit is very tight fitting to avoid displacement of markers during movement. However, as a result, some subjects were reluctant to wear the suit. To solve this problem, the researchers told the subjects a story about going on a space mission in order to increase their willingness to wear the suit. All subjects were easily persuaded to don the ‘‘space suit’’ and participate. The motion analysis technology used in this study cannot capture the finer finger movements, so finger coordination was not included in this study. M-ABC, BOTMP and SIPT all have items relating to finger movements, which are not included in this study. In addition, all children in this study were Taiwan kindergarten students with normal development. Future research may focus on the test’s validity for different groups, such as those with developmental delay. 5. Conclusions This study investigates the validity of the computerized bilateral motor coordination test in children aged 4–6 years. In the bilateral coordination movement subtest, there is an average accuracy of 83.9%, a sensitivity of 86.4%, and a specificity of 83.1%, respectively. In the projected action subtest, there is an average accuracy of 90.5%, a sensitivity of 88.1%, and a specificity of 90.4%, respectively. The computerized bilateral motor coordination test shows an average accuracy of 86.3%, a sensitivity of 87.0%, and a specificity of 85.8%. The results show that the computerized bilateral motor coordination test is a valid diagnosis tool to use in assessing bilateral coordination of children. Therefore, the tool may be used to screen children for bilateral coordination impairments and diagnose poor bilateral coordination in a clinical setting. Conflict of interest The authors have no conflict of interest to declare. Acknowledgements The authors would like to thank the National Science Council of Taiwan (Grant No. 100-2410-H-142-005) for supporting the data collection and (Grant No. 101-2410-H-142-005-MY3) for supporting the editing service of the manuscript. References Ayres, A. J. (1989). Sensory integration and praxis tests. Los Angeles: Western Psychological Services. Bruininks, R. H. (2005). Bruininks-Oseretsky test of motor proficiency (BOT-2). Minneapolis, MN: Pearson Assessment. Bundy, A. C., Lane, S. J., & Murray, E. A. (2002). Sensory Integration theory and practice (2nd ed.). Philadelphia, PA: Davis Company. Cael, C. (2010). Functional anatomy = musculoskeletal anatomy, kinesiology, and palpation for manual therapists. Philadelphia: Wolters Kluwer/Lippincott, Williams & Wilkins. Cardoso, A. A., & Magalhaes, L. d. C. (2009). Bilateral coordination and motor sequencing in Brazilian children: Preliminary construct validity and reliability analysis. Occupational Therapy International, 16(2), 107–121. Cermak, S. A., Trimble, H., Coryell, J., & Drake, C. (1990). Bilateral motor coordination in adolescents with and without learning disabilities. Physical & Occupational Therapy in Pediatrics, 10(1), 5–18. Cocks, N., Barton, B., & Donelly, M. (2009). Self-concept of boys with developmental coordination disorder. Physical & Occupational Therapy in Pediatrics, 29(1), 6– 22. Desrosiers, J., Rochette, A., & Corriveau, H. (2005). Validation of a new lower-extremity motor coordination test. Archives of Physical Medicine and Rehabilitation, 86(5), 993–998. Fournier, K. A., Hass, C. J., Naik, S. K., Lodha, N., & Cauraugh, J. H. (2010). Motor coordination in autism spectrum disorders: A synthesis and meta-analysis. Journal of Autism and Developmental Disorders, 40(10), 1227–1240. Gonzalez, R. C., Woods, R. E., & Eddins, S. L. (2009). Digital image processing using MATLAB (2nd ed.). Gatesmark Publishing. Henderson, S. E., & Sugden, D. A. (1992). Movement assessment battery for children. London: The Psychological Corporation. High, J., Gough, A., Pennington, D., & Wright, C. (2000). Alternative assessments for sensory integration dysfunction. British Journal of Occupational Therapy, 63(1), 2–8. Hu, W., Tan, T., Wang, L., & Maybank, S. (2004). A survey on visual surveillance of object motion and behaviors. IEEE Transactions on Systems, Mans, and CyberneticsParts: Applications and Reviews, 34(3), 334–352. Huh, J., Williams, H. G., & Burke, J. R. (1998). Development of bilateral motor control in children with developmental coordination disorders. Developmental Medicine and Child Neurology, 40(7), 474–484. Kuncheva, L. I. (2004). Combining pattern classifiers: Methods and algorithms. New Jersey: Wiley and Sons. Magalhaes, L. C., Koomar, J. A., & Cermak, S. A. (1989). Bilateral motor coordination in 5- to 9-year-old children: A pilot study. American Journal of Occupational Therapy, 43(7), 437–443. Piek, J. P., Pitcher, T., & Hay, D. A. (1999). Motor coordination and kinaesthesis in boys with attention deficit-hyperactivity disorder. Developmental Medicine and Child Neurology, 41, 159–165. Poulsen, A. A., Johnson, H., & Ziviani, J. M. (2011). Participation, self-concept and motor performance of boys with developmental coordination disorder: a classification and regression tree analysis approach. Australian Occupational Therapy Journal, 58(2), 95–102. Rodger, S., Watter, P., Marinac, J., Woodyatt, G., Ziviani, J., & Ozanne, A. (2007). Assessment of children with developmental coordination disorder (DCD): Motor, functional, self-efficacy and communication abilities. New Zealand Journal of Physiotherapy, 35(3), 99. Watter, P. (2006). Movement assessment battery for children (movement ABC). Australian Journal of Physiotherapy, 52(1), 68.

Development and validation of the computerized bilateral motor coordination test.

The purpose of this study was to explore the validity of computerized scaling of bilateral, motor coordination in children 4-6 years of age. There wer...
595KB Sizes 0 Downloads 0 Views