WB system (Waseda Bioinstrumentation system)

  1. Objective
  2. Background
  3. System overview
  4. Applications
  5. History
  6. Acknowledgments

1. Objective

The goal of our research is to develop a portable Bioinstrumentation System that can objectively measure human full body motion. This system is the base to define a set of parameters to characterize numerically human movement, and to develop objective evaluation tools to measure movements during selected tasks, to compare differences and analyse data history to evaluate performances trends.

2. Background

In recent years there has been an increasing amount of research and development of technologies and methods to analyse and quantify body movement, in a variety of fields for different applications. Automatic human movement sensing technology is called motion capture, and respond to the fundamental necessity of a better understanding of the performance of human being in several situations, to clarify not simply what a skilled (or healthy) person does better than a novice (or patient), but also how.

Motion capture obtains motion data from human performers, tracks their key points/joints movement, and translate them into a digital model, to analyse in detail the performance characteristics. Motion capture systems are commonly divided in these three categories:

1) camera-based motion capture systems
2) magnetic-based motion capture system
3) inertial-sensor-based motion capture system

Each of these systems presents several drawbacks, and choosing the appropriate one is difficult and depends on many factors. Camera-based systems are very expensive and can be used only in a calibrated room; the markers they need are heavy and bulky and need to be always in sight on the cameras, which is not always possible. Magnetic-based systems have magnetic distortion problems and position data are acquired at a relatively low frequency, thus limiting the precision of the analysis. Current inertial-sensor-based systems are too big for most practical applications, because they hinder free movement.
None of the current systems, therefore, fit the requirements of motion capture for applications such as Minimally Invasive Surgery (MIS), neurosurgery, gait analysis, rehabilitation, where precision is a critical requirement.

Our group's mission is to fill this technology gap, developing a motion capture system for precision applications, minimally invasive, relatively inexpensive, and reconfigurable or expandable to include measurement of side physiological parameters, a perfect sensor integration to have a complete and synchronized image of the human body state during movement.

3. System overview (Inertial Measurement Unit)

Fig. 1 WB-3 IMU

Fig. 1 WB-3 IMU

Fig. 2 WB-4 IMU

Fig. 2 WB-4 IMU

Due to its versatility and relative low-cost, we opted for an inertial-sensor-based motion capture system. We developed ultra-miniaturized wearable sensors that can be integrated and reconfigured depending on the application and on the human subject anthropometric characteristics. Our system has two types of configurations: a wired one, based on CANBUS data transmission, and a completely wireless one, based on standard Bluetooth transmission. In both configurations, data are eventually transmitted via Bluetooth to a remote computer for data log and analysis. However, in the wireless configuration each sensor has a separate miniaturized battery unit and transmits data independently, whilst in the wired configuration sensors are all connected to a central board slightly bulkier containing a powerful battery, which collects all data and sends them at once. The wireless configuration is better for applications that require few sensors, greater freedom of movement and short recording time. For applications requiring continuous logging for a long time, the wired configuration is more suitable.

Current sensors include a 9-axis Inertial Measurement Unit (IMU), containing a 3-axis accelerometer sensor, a 3-axis gyroscope, and a 3-axis magnetometer; and an Electromyography sensor unit (EMG). Both sensor units contain a 32-bit microcontroller STM32 Cortex (STMicroelectronics) for embedded signal elaboration.

4. Applications

5. History

WB-1 (2004)

WB-1R (2005)

WB-2

WB-2 (2007)

WB-3

WB-3 (2009)

WB-3R

WB-3R (2010)

WB-3R

WB-4R (2014)

6. Acknowledgments

This work was supported in part by Global COE Program "Global Robot Academia", MEXT, Japan. This research has been also partially supported by several grants by STMicroelectronics, which also provided the core sensors, microcontrollers, and development boards; and by Wurth Elektronik, which provided connectors, cables, and other components. Partial support received also from: the Advancement of University Education Project of Chinese government Grant # [2007] - 3020; the JSPS Grant-in-aid for Scientific Research #19700389 and #20700386; S-COE ASMeW - Consolidated Research Institute for Advanced Science and Medical Care, Waseda University; ASMeW Priority Research B Grant #11; ASMeW Priority Research C Grant #11; the Waseda University Grant for Special Research Projects (No. 266740); the JSPS Postdoctoral Fellowship Program for Foreign Researcher FY2008, and the MEXT scholarship for Foreign Students FY2012. The authors would also like to express their thanks to the Italian Ministry of Foreign Affairs, General Directorate for Cultural Promotion and Cooperation, for its support to RoboCasa. The authors would also like to express their gratitude to Okino Industries LTD, Japan ROBOTECH LTD, SolidWorks Corp., Dyden, for their support to the research.

Last Update: 2016-11-01
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