**3.1 System architecture**

Different types of noninvasive sensors are able to measure the gait kinematics, such as magnetic sensors, goniometers, and inertial measurement units (IMU). These IMUs, consisting of sensors, measure the acceleration, the angular velocity, and the terrestrial magnetic field density around the sensor in the orthonormal coordinate system bound to the sensors. This information is used to estimate the orientation of the human body segments on which the sensors are placed. The joint angles are then calculated based on the orientations of the segments.

The IMU and compass sensor based on MEMS (Micro Electro Mechanical System) technology allow the design of miniaturized wireless sensors respecting the constraints of energy consumption, compactness, and cost. Therefore, the system uses MEMS IMU and compass sensor to capture the movement of lower limb segments.

The system comprises at least seven sensor nodes as shown in **Figure 3**. Each node is built around the System-on-Chip (SoC) Nrf51822 from Nordic Semiconductors. It offers many low-power wireless communication options, including ESB and Bluetooth Low Energy (BLE) protocols. The inertial sensor used is the MPU6050 from Invensense. This IMU integrates a 3D accelerometer and a 3D gyrometer. A 3D magnetometer is used to measure the Earth's magnetic field. Measurements carried out by the sensors are processed by the onboard SoC to estimate their orientations in real time.

A coordinator node supports the synchronization of the sensor nodes, the recording of the data coming from the sensor nodes on a SD card, and the management of the various functions of the sensor node (connection/disconnection,

**145**

*An Embedded Gait Analysis System for CNS Injury Patients*

**3.2 Constraints related to the use of a wireless device**

calibration, and power on/off). The sensor nodes wait for synchronization with the coordinator and then transmit the data to it. This wireless distributed system architecture provides great system flexibility and greatly improves its ease of use.

The wireless transmission protocol, in addition to being energy efficient, must have enough bandwidth to transmit measurements in accordance with the required sampling frequency. The protocol must allow synchronization of the clocks of the various sensors to have the same time reference. Clock synchronization, imperative in our application, allows separate systems to have the smallest possible difference between their subjective times whatever the factors that can modify the

Candidate technologies, such as WIFI (IEEE 802.11), ZigBee (IEEE 8.2.15.4),

Without the time synchronization, the time shift between sensors may achieve 144 ms after 1 hour of measurement using a clock with accuracy equal to 20 ppm. Synchronization accuracy tests were performed. The synchronization RMSE calculated during the last minute after 1 hour of recording is equal to 18.2 μs. During the

The average of the sampling period of the system, i.e. the duration between two synchronizations, equals 9.1 ms with a standard deviation of 1.1 ms. The acquisition

Each sensor node has its own reference system. It is then necessary to define a suitable coordinate system to describe the orientation of a lower limb's segment. Two coordinate systems are used in this application. One system is fixed to the earth and may be considered for the purpose of segment of human motion analysis to be an inertial coordinate system. The other coordinate system is local to the IMU and is referred to as a body coordinate system. The attitude of an object can be represented in different ways [24]. Euler angles, rotation matrix, and quaternion are the most used methods. Quaternion is difficult to understand but compared to the two other representation methods, it requires less memory and calculation capabilities. It avoids the problem of Gimbal lock that appears in Euler angle representation. The quaternion representation is used in this application. A complete description of the use of quaternions for articular angle calculation between two segments and the transformation of the local coordinate system to the terrestrial reference is

Data captured by IMU and magnetometer are processed in real time with the algorithm executed by the onboard SoC to estimate sensor attitude. This algorithm uses a numerical integration to compute the angle from the angular velocity provided by the gyrometer. This numerical integration inevitably introduces a drift in addition to the calculation approximation error. To correct this drift which accumulates over time, the information provided by the accelerometer and the magnetometer have been merged according to the onboard algorithm. The detail of

Bluetooth classic, BLE, GSM, 3G, and LTE, have not been selected because either they do not allow a precise synchronization of the sensor nodes, or they do not provide the desired throughput or limit the number of nodes. The chosen protocol, ESB, is a proprietary low energy consumption protocol proposed by Nordic Semiconductor with a bit rate of 2 Mbps. It reaches a transmission speed of

1.2 Mbps. It supports broadcast functionality to synchronize clocks.

test, the maximum clock offset between two sensor nodes is 37.6 μs.

frequency of system locomotive parameters can reach 109 Hz.

*DOI: http://dx.doi.org/10.5772/intechopen.83826*

time reference [23].

**3.3 Joint angle reckoning**

described in [24, 25].

this algorithm is described in [26, 27].

**Figure 3.** *System organization and sensor placement.*

*Assistive and Rehabilitation Engineering*

the experimentation section.

**3.1 System architecture**

limb segments.

estimate their orientations in real time.

**3. Recording of gait parameters by wireless wearable system**

angles are then calculated based on the orientations of the segments.

The main objective at the base of the approach is the study of the signals from the sensors during walking and the implementation of the posture estimation algorithm. This section describes the architecture of the realized prototype as well as the algorithm used to estimate the posture. The flexions and extensions of the segments estimated by the prototype are compared with the measurements from the 3D-GA system considered as a reference. The results of this comparison will be shown in

Different types of noninvasive sensors are able to measure the gait kinematics, such as magnetic sensors, goniometers, and inertial measurement units (IMU). These IMUs, consisting of sensors, measure the acceleration, the angular velocity, and the terrestrial magnetic field density around the sensor in the orthonormal coordinate system bound to the sensors. This information is used to estimate the orientation of the human body segments on which the sensors are placed. The joint

The IMU and compass sensor based on MEMS (Micro Electro Mechanical System) technology allow the design of miniaturized wireless sensors respecting the constraints of energy consumption, compactness, and cost. Therefore, the system uses MEMS IMU and compass sensor to capture the movement of lower

The system comprises at least seven sensor nodes as shown in **Figure 3**. Each node is built around the System-on-Chip (SoC) Nrf51822 from Nordic Semiconductors. It offers many low-power wireless communication options, including ESB and Bluetooth Low Energy (BLE) protocols. The inertial sensor used is the MPU6050 from Invensense. This IMU integrates a 3D accelerometer and a 3D gyrometer. A 3D magnetometer is used to measure the Earth's magnetic field. Measurements carried out by the sensors are processed by the onboard SoC to

A coordinator node supports the synchronization of the sensor nodes, the recording of the data coming from the sensor nodes on a SD card, and the management of the various functions of the sensor node (connection/disconnection,

**144**

**Figure 3.**

*System organization and sensor placement.*

calibration, and power on/off). The sensor nodes wait for synchronization with the coordinator and then transmit the data to it. This wireless distributed system architecture provides great system flexibility and greatly improves its ease of use.
