Polycystic Ovarian Syndrome (PCOS), is a condition of the ovary consisting numerous follicles. Accurate size and number of follicles detected are crucial for treatment. Hence the diagnosis of this condition is by measuring and calculating the size and number of follicles existed in the ovary. For diagnosis, ultrasound imaging has become an effective tool as it is non-invasive, inexpensive and portable. However, the presence of speckle noise in ultrasound imaging has caused an obstruction for manual diagnosis which are high time consumption and often produce errors. Thus, image segmentation for ultrasound imaging is critical to identify follicles for PCOS diagnosis and proper health treatment. This paper presents different methods proposed and applied in automated follicle identification for PCOS diagnosis by previous researchers. In this paper, the methods and performance evaluation are identified and compared. Finally, this paper also provided suggestions in developing methods for future research.
Over recent years, the reseach in the field of soft actuation has been extensively increased for achieving more complex motion path with smooth, high flexible movement and high generated force at minimum operating pressure. This paper presents the study on gripping force capability of soft actuators applied on glove-type finger exoskeleton, developed in motivation to assist individuals having weak finger gripping ability in their rehabilitation exercise towards hand function restoration. The exoskeleton utilizes five cylindrical shaped pneumatic bending actuators developed in the lab, which use fiber reinforcement as a cause of bending motion that drive finger’s flexion movement. Four right-handed healthy volunteers simulated paralysis participated in the study. At 200kPa safe operating pressure, the soft exoskeleton worn by the subjects demonstrates the ability to provide adequate grip force. The grip force generated from exoskeleton worn on passive right hand is 4.66 ± 0.2 N and 3.61± 0.2 N from passive left hand, both higher than the minimum grip forces measured to hold the Hand Dynamometer of 240 g. It shows good potential to be used as a finger rehabilitation assist device.
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