Recognition of elementary arm movements using orientation of a tri-axial accelerometer located near the wrist

Abstract

Abstract:In this paper we present a method for recognising three fundamental movements of the human arm (reach and retrieve, lift cup to mouth, rotation of the arm) by determining the orientation of a tri-axial accelerometer located near the wrist. Our objective is to detect the occurrence of such movements performed with the impaired arm of a stroke patient during normal daily activities as a means to assess their rehabilitation. The method relies on accurately mapping transitions of predefined, standard orientations of the accelerometer to corresponding elementary arm movements. To evaluate the technique, kinematic data was collected from four healthy subjects and four stroke patients as they performed a number of activities involved in a representative activity of daily living, 'making-a-cup-of-tea'. Our experimental results show that the proposed method can independently recognise all three of the elementary upper limb movements investigated with accuracies in the range 91%-99% for healthy subjects and 70%-85% for stroke patients.

Hand hygiene duration and technique recognition using wrist-worn sensors

“…Previous efforts to discern hand motions using simple wristbased sensors have focused on very basic motions like drinking [18], eating [19], or smoking [20]. Those that examined more complex motions relied upon more sophisticated sensing methods such as electromyographic (EMG) sensors [21], or multiple sensors placed throughout the body to form body-area networks [22,23].…”

“…• From 70-99% using thresholds and the sequence of orientations to recognize three simple motions such as reaching out to retrieve an item [18].…”

Recognition of activities of daily living based on the vertical displacement of the wrist

“…[4,5,6]. The second approache is based on body-mounted sensors for ambulatory monitoring [7,8,9,10,11,12,13]. This approach have become the preferred method with inertial sensors as the detection device, such as accelerometers and gyroscopes.…”

Real-time arm movement recognition using FPGA

“…Therefore, the above mentioned recognition techniques may not always be applicable for real-time continuous operations using WSN nodes. This therefore motivated us to implement the lowcomplexity movement recognition methodology developed in [8] on an FPGA with a view towards real-time detection of arm movements as a proof-of-concept methodology.…”

“…The algorithm presented in [8] works by mapping six standard orientations of a tri-axial accelerometer to the corresponding arm movements investigated. The methodology works by predicting the most likely orientation of the sensor module at any particular time by assessing which of the three accelerometer axes is the most active at that time.…”