A virtual blind cane system for indoor application, including a camera, a line laser and an inertial measurement unit (IMU), is proposed in this paper. Working as a blind cane, the proposed system helps a blind person find the type of obstacle and the distance to it. The distance from the user to the obstacle is estimated by extracting the laser coordinate points on the obstacle, as well as tracking the system pointing angle. The paper provides a simple method to classify the obstacle’s type by analyzing the laser intersection histogram. Real experimental results are presented to show the validity and accuracy of the proposed system.

Stooping is a posture which is described as an involuntary forward bending of the thoracolumbar spine. Conventionally, the stooped posture (SP) in Parkinson’s disease patients is measured in static or limited movement conditions using a radiological or optoelectronic system. In the dynamic condition with long movement distance, there was no effective method in preference to the empirical assessment from doctors. In this research, we proposed a practical method for estimating the SP with a high accuracy where accelerometers can be mounted on the neck or upper back as a wearable sensor. The experiments with simulated subjects showed a high correlation of 0.96 and 0.99 between the estimated SP angle and the reference angles for neck and back sensor position, respectively. The maximum absolute error (0.9 and 1.5 degrees) indicated that the system can be used, not only in clinical assessment as a measurement, but also in daily life as a corrector.

Stooped posture, which is usually aggravated during walking, is one of the typical postural deformities in patients with parkinsonism. However, the degree of stooped posture is difficult to quantitatively measure during walking. Furthermore, continuous feedback on posture is also difficult to provide. The purpose of this study is to measure the degree of stooped posture during gait and to investigate whether vibration feedback from sensor modules can improve a patient’s posture. Parkinsonian patients with stooped posture were recruited for this study. Two wearable sensors with three-axis accelerometers were attached, one at the upper neck and the other just below the C7 spinous process of the patients. After being calibrated in the most upright posture, the sensors continuously recorded the sagittal angles at 20 Hz and averaged the data at every second during a 6 min walk test. In the control session, the patients walked with the sensors as usual. In the vibration session, sensory feedback was provided through vibrations from the neck sensor module when the sagittal angle exceeded a programmable threshold value. Data were collected and analyzed successfully in a total of 10 patients. The neck flexion and back flexion were slightly aggravated during gait, although the average change was <10° in most patients in both measurement sessions. Therefore, it was difficult to evaluate the effect of sensory feedback through vibration. However, some patients showed immediate response to the feedback and corrected their posture during gait. In conclusion, this preliminary study suggests that stooped posture could be quantitatively measured during gait by using wearable sensors in patients with parkinsonism. Sensory feedback through vibration from sensor modules may help in correcting posture during gait in selected patients.

Golf Green Slope Estimation Using a Cross Laser Structured Light System and an Accelerometer Golf slope estimation;Accelerometer;Structured light; In this paper, we propose a method combining an accelerometer with a cross structured light system to estimate the golf green slope. The cross-line laser provides two laser planes whose functions are computed with respect to the camera coordinate frame using a least square optimization. By capturing the projections of the cross-line laser on the golf slope in a static pose using a camera, two 3D curves’ functions are approximated as high order polynomials corresponding to the camera coordinate frame. Curves’ functions are then expressed in the world coordinate frame utilizing a rotation matrix that is estimated based on the accelerometer’s output. The curves provide some important information of the green such as the height and the slope’s angle. The curves estimation accuracy is verified via some experiments which use OptiTrack camera system as a ground-truth reference.