Keywords

1 Introduction

Balance ability is divided into static balance ability to maintains a certain posture on a fixed surface and dynamic balance ability to maintain a posture while performing movement. This is fundamental for normal daily activities and maintained through diverse interactions between musculoskeletal system and nervous system [1, 2]. The elderly population is growing as Korea becomes an aging society recently. These elder people or people with wrong life or exercise habits increasingly experience problems in their balance ability. The aging-caused muscle strength reduction and muscular atrophy rapidly undermine balance ability, causing brain damage or fracture by fall [3, 4]. Moreover, since wrong life or exercise habits are repeated unconsciously, they could cause a problem in muscular function and balance ability leading to musculoskeletal diseases such as spinal deformity, left-right shoulder imbalance, and twisted pelvis [5]. Methods to prevent such diseases include core muscle reinforcement exercise that balances the body and holds the spine and pelvis not to be shaken [6]. This exercise is to help enhance the body joint motion range, flexibility, muscular strength, endurance, coordination, etc. Methods include that a therapist induces certain postures and their repetition or that a patient looks in a mirror to see his or her own moves to train [7, 8]. Such training methods are to repeat simple moves and do not tell patients about any quantitative change in their present status in real time. In addition, the boredom of such a training method undermines patients’ voluntary engagement or training flow [9]. For this reason, motivational ways of exercise have been proposed for voluntary training engagement, which form scenarios for patients to enjoy their training with fun by giving contents in connection with devices measuring their body movements [10, 11].

In this study, wireless IMU sensor was employed to develop an analysis program that measures the joint motion range before and after the balance training of sagittal plane, coronal plane and transverse plane; and compares changes. This study sought to utilize this program to analyze users’ physical measurement data and recommend efficient training contents according to the degree of their physical imbalance.

2 Methods and Results

2.1 Range of Motion (ROM) Measurement Program

Figure 1(a) shows the status of attaching to body the IMU sensor (LP-Research’s LPMS-B2) for ROM measurement and contents implementation in this study. Here, the IMU sensor wirelessly transmits each value of acceleration, angular speed, Euler angle, and Quaternion angle using Bluetooth in real time; thus, it can measure ROM and physical movement without any spatial restriction. ROM is measured in order of, as in Fig. 1(b), a user’s coronal, sagittal, and transverse planes. Their Euler angle values are measured in real time then, the max Euler angle values are extracted at each direction. The max angle values extracted from here are utilized as parameters necessary to determine the difficulty level of training contents. Training contents at an appropriate difficulty level for users’ body balance status gives users the sense of achievement for their body balance improvement and is also an efficient way. Moreover, users’ ROM results are measured at every direction in real time and the saved data are visually presented for everyone to check their present body balance status easily and compare pre/post-training change in ROM.

Fig. 1.
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(a) Location of IMU attached to the body (b) Flow chart of ROM measurement

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ROM measurement in the coronal, sagittal, and transverse planes are shown in Fig. 2. shows the left/right motion range measurement in the coronal plane. First, when the Test button is pressed, Euler angle is measured for the 2 s when a posture is maintained and their mean value is set as the reference value for the corresponding user’s ROM measurement. This value is utilized to represent a user’s max ROM measured via coronal left/right turn. In Fig. 2(a), the pie graph in the screen center visualizes ROM in real time. The red-colored area represents the presently-measured max motion range. With respect to the coronal left/right-side ROM, the red-colored bar represents the presently-measured ROM; and green bar, previously-measured motion range mean. Figure 2(b) and (c) show the ROM measurement in the sagittal and transverse planes just as the measurement method in the coronal plane.

Fig. 2.
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Motion range measurement (a) coronal (b) sagittal (c) transverse (Color figure online)

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After the measurement of coronal, sagittal, transverse Euler Angle values is generally completed, the results are presented in Fig. 3. The result page shows up/down or three-directional left/right ROM in bar graph. The presently-measured values are red colored and previous mean values, green colored. Users can check their motion range in each direction in real time. The measured Euler Angle values are saved in the internal DB and utilized to compare pre/post-interventional ROM changes. Max Euler Angle value is employed as a parameter to determine content difficulty levels.

Fig. 3.
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Result page of ROM measurement

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2.2 Body Balance Ability Training Contents

Balance ability training contents were made for users to select necessary training programs or receive recommendations based on the motion range measurement results. In the system, a character was utilized to follow the move of users to help improve their interest and flow while implementing the contents for proactive training engagement. During the content move to maintain balance on unstable platform, users do the trunk exercise reinforcing their core muscles. Physical movements are measured with IMU sensor and the moves are mapped to the moving route of the character. Figure 4(a) is the main contents execution page. After clicking Start, users can select a training direction they wish as in Fig. 4(b) then follow the corresponding training. The materialized contents support 5 modes (Auto, Front, Rear, Left, Right). The Auto mode allows a user to train his or her weak direction based on the ROM values. As presented in Fig. 4(c), training difficulty was differentiated into Easy, Normal and Hard. As the difficulty level moves up, users have smaller-sized mission objects and character requiring more detailed moves to keep a posture.

Fig. 4.
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Basic Screen Construction (a) Start (b) Training Mode Selection (c) Difficulty Setting

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Figure 5 shows a content screen where an Indian character eats cheese. In Fig. 5(a), the Indian character follows the move of a user and the user has to move the character to the cheese and keep a posture for 2 s to win the cheese. Then, while moving to the house in the center of the page as in Fig. 5(b), the user has to repeat the content 5 times for posture arrangement. The figures on the upper right part of the page informs the number of present round of ongoing work. The Pause button allows users to suspend the game if they feel any difficult.

Fig. 5.
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Content page following users’ move

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3 Conclusions

In this study, a program was developed based on wireless IMU sensor, which measures the ROM of pre/post-training of sagittal, coronal, and transverse planes; and compares any changes in there. The developed program allows users to measure their max turn range in each area and check their status; and sets up the necessary training mode for each user automatically in connection with training contents. In this manner, users can follow training contents at an appropriate difficulty level for their own status and, by receiving the necessary training intensively, training process efficiency can elevate. Moreover, pre/post-training change in motion range can help increase users’ sense of achievement and motivation to encourage proactive training engagement. The training contents aim at reinforcing the core muscles for enhanced balance ability. In the training, IMU sensor is attached to the body and Euler angle is measured to move the content character to a target. In order for users to fully enjoy the contents, diverse kinds of modes are provided at different difficulty levels so that users can select an appropriate training program for themselves or receive recommendation to enjoy training with high efficiency. Together with the motion range measurement developed in the present study, pressure sensor will be employed to measure plantar pressure and understand balance ability in diversified aspects in further research. By doing so, users’ present status will be more precisely analyzed and enhancement in personalized training recommendation will be additionally studied.