Abdullatif Alwasel

Sensing Construction Work-Related Musculoskeletal Disorders (WMSDs)

Much of the developed world’s construction workforce is increasing in average age, and yet construction workers typically retire well before they reach the age of sixty. One reason is that their bodies are worn out because of the nature of the work. We therefore face the challenge of both reducing their physical stress and increasing their productive work life, if we wish to avert an economic and social crunch given the demographic trends towards an aging population in most developed countries. In particular, recent statistics from the U.S Department of labor show that 6.9% of all Workrelated Musculoskeletal Disorders (WMSDs) among workers in 2008 affected shoulders; this percentage becomes much larger for electricians, carpenters, and related construction crafts. The cost to our industry and to society is huge, and it is unnecessary. Reduction of certain types of movements and improvements in posture can result in reduced rates of shoulder WMSDs and in extended work lives. This can be done with a combination of robotics, work re-design, and work monitoring. This paper provides the statistical background and economic analysis that supports the scope of the problem, presents background on the kinematics of shoulder movement, and explains the biomechanics and causes of shoulder injuries. Then, preliminary results are presented for a prototype of a simple, low-cost, sensing solution for automatically monitoring undesirable movements and patterns of motion. It is expected that this could be broadly implemented to help reduce Construction Work-related Musculoskeletal Disorders (WMSDs).

A Human Body Posture Sensor for Monitoring and Diagnosing MSD Risk Factors

Musculoskeletal disorders (MSDs) threaten the wellbeing and livelihood of a large number of construction workers incurring a significant cost to society. We present a new method to monitor and diagnose MSD risks in the workplace. The sensing unit of the system is an optical encoder encompassed within a non-intrusive exoskeleton to measure the joint angle of interest. This sensor can be applied to ball-and-socket and hinge-type joints of the human body, such as the shoulder, elbow, and knee joints. The system is contactless and does not require markers or cameras. Angle measurements are acquired directly without mathematical post-processing, thereby avoiding numerical noise and drift challenges. The system is a simple, robust, and deployable, but it currently lacks resolution of parallel degrees of freedom.

Fatigue Detection Using Phase-Space Warping

A novel application of phase-space warping (PSW) method to detect fatigue in the musculoskeletal system is presented. Experimental kinematic, force, and physiological signals are used to produce a fatigue metric. The metric is produced using time-delay embedding and PSW methods. The results showed that by using force and kinematic signals, an overall estimate of the muscle group state can be achieved. Further, when using electromyography (EMG) signals the fatigue metric can be used as a tool to evaluate muscles activation and load sharing patterns for individual muscles. The presented method will allow for fatigue evolution measurement outside a laboratory environment, which open doors to applications such as tracking the physical state of players during competition, workers in a plant, and patients undergoing in-home rehabilitation.

A Technique to Detect Fatigue in the Lower Limbs

As muscles fatigue, their passive and active mechanical properties change increasing the susceptibility of the human body to damage. The state-of-the-art technique for muscle fatigue detection, EMG signals, is cumbersome. This paper presents a technique to detect fatigue by tracking a kinematic parameter of the musculoskeletal system. The method uses the time-history of a single joint angle to detect fatigue in the lower limbs. A sensor is mounted to the knee joint to measure the knee flexion angle. Time delay embedding is used to track the orbit of knee joint motions in a reconstructed phase-space. The reconstructed phase-space allows us to obtain information about other body parts and joints of the lower limb in addition to the knee joint, since they are all connected in an open kinematic chain. Long-time drift in the orbit location and shape in phase-space is quantified and used as a measure of lower limb fatigue. The proposed technique presents a mobile, wireless, and cheap method to assess fatigue that can act as an early warning system for the lower limb.