Aqilah Leela T. Narayanan

Chemopreventive effect of apple and berry fruits against colon cancer

Colon cancer arises due to the conversion of precancerous polyps (benign) found in the inner lining of the colon. Prevention is better than cure, and this is very true with respect to colon cancer. Various epidemiologic studies have linked colorectal cancer with food intake. Apple and berry juices are widely consumed among various ethnicities because of their nutritious values. In this review article, chemopreventive effects of these fruit juices against colon cancer are discussed. Studies dealing with bioavailability, in vitro and in vivo effects of apple and berry juices are emphasized in this article. A thorough literature survey indicated that various phenolic phytochemicals present in these fruit juices have the innate potential to inhibit colon cancer cell lines. This review proposes the need for more preclinical evidence for the effects of fruit juices against different colon cancer cells, and also strives to facilitate clinical studies using these juices in humans in large trials. The conclusion of the review is that these apple and berry juices will be possible candidates in the campaign against colon cancer.

Development of CR2-Haptic: A compact and portable rehabilitation robot for wrist and forearm training

Stroke has now become the leading cause of severe disability. Rehabilitation robots are gradually becoming popular for stroke rehabilitation to improve motor recovery, as robotic technology can assist, enhance, and further quantify rehabilitation training for stroke patients. However, most of the available rehabilitation robots are complex and involve multiple degrees-of-freedom (DOFs) causing it to be very expensive and huge in size. Rehabilitation robots should be useful but also need to be affordable and portable enabling more patients to afford and train independently at home. This paper presents a development of an affordable, portable and compact rehabilitation robot that implements different rehabilitation strategies for stroke patient to train forearm and wrist movement in an enhanced virtual reality environment with haptic feedback.

A novel haptic interface and control algorithm for robotic rehabilitation of stoke patients

Rehabilitation robots are gradually becoming popular for stroke rehabilitation to improve motor recovery. By using a robot, the patient may perform the training more frequently on their own, but they must be motivated to do so. Therefore, this project develops a set of rehabilitation training programs with different haptic modalities on Compact Rehabilitation Robot (CR2) - a robot used to train upper and lower limbs reaching movement. The paper present the developed haptic interface, Haptic Sense with five configurable haptic modalities that include sensations of weight, wall, spring, sponge and visual amplification. A combination of several haptic modalities was implemented into virtual reality games, Water Drop - a progressive training game with up to nine levels of difficulties that requires user to move the cup to collect the water drops.

Portable and Reconfigurable Wrist Robot Improves Hand Function for Post-Stroke Subjects

Rehabilitation robots have become increasingly popular for stroke rehabilitation. However, the high cost of robots hampers their implementation on a large scale. This paper implements the concept of a modular and reconfigurable robot, reducing its cost and size by adopting different therapeutic end effectors for different training movements using a single robot. The challenge is to increase the robot’s portability and identify appropriate kinds of modular tools and configurations. Because literature on the effectiveness of this kind of rehabilitation robot is still scarce, this paper presents the design of a portable and reconfigurable rehabilitation robot and describes its use with a group of post-stroke patients for wrist and forearm training. Seven stroke subjects received training using a reconfigurable robot for 30 sessions, lasting 30 min per session. Post-training, statistical analysis showed significant improvement of 3.29 points (16.20%, p = 0.027) on the Fugl-Meyer assessment scale for forearm and wrist components. Significant improvement of active range of motion was detected in both pronation-supination (75.59%, p = 0.018) and wrist flexion-extension (56.12%, p = 0.018) after the training. These preliminary results demonstrate that the developed reconfigurable robot could improve subjects’ wrist and forearm movement.

iRest: Interactive rehabilitation and assessment tool

The ability to perform activities of daily living such as eating, drinking or writing is limited after a stroke. Rehabilitation is to encourage the recovery process and to define effective rehabilitation procedures, quantitative assessment should be included. Conventional assessment scales such as Fugl-Meyer and Motor Assessment Scale have several limitations as the scales are subjective, provide only rough estimates, and are highly dependent on the ability of the trained physiotherapist; making it difficult to quantify impairment and disability. Using these methods, small changes due to stroke are often undetected. Therefore, precise and objective measurement of motor impairment is needed to monitor and quantify the patients progress. This paper presents the design and development of an interactive rehabilitation and assessment tool, iRest. This system does not use any robotic actuator but only uses a small DC motor to generate vibration. Three robotic assessment modules were developed as a virtual reality (VR) environments namely Draw I, Draw Diamond and Draw Circle. The design of this VR considers the required movement in activities of daily living, including isolated and combined movements.

Comparison of two sagittal pelvic tilt measurement protocols using newly calibrated novel pelvic sensor

Pelvic tilt posture is the key to ideal standing posture, yet no accurate quantitative measurements with standardized protocols have been implemented. The aim of the current study was to assess the calibration of a newly developed pelvic tilt sensor and to compare the repeatability using 2 protocols. Pelvic tilt was measured in a healthy woman with two different protocols and two repeated test were carried out for each protocol by a single tester. Repeatability testing for sagittal pelvic tilt was measured during neutral standing (NP), maximal anterior pelvic tilt (APT), and maximal posterior pelvic tilt (PPT). The newly developed pelvic tilt sensor was calibrated manually with a goniometer and indicated excellent correlation (r=0.99). NP, APT, and PPT in protocol 1 showed poor intra-class correlation (ICCs) compared to protocol 2 which showed high ICCs (r≥0.90) and low standard error of measurement (SEM). The excellent results obtained using the newly developed pelvic sensor in protocol 2 shows that it can be potentially used in clinical practice.

The potential of iRest in measuring the hand function performance of stroke patients

BACKGROUND Clinical scales such as Fugl-Meyer Assessment (FMA) and Motor Assessment Scale (MAS) are widely used to evaluate stroke patients motor performance. However, there are several limitations with these assessment scales such as subjectivity, lack of repeatability, time-consuming and highly depend on the ability of the physiotherapy. In contrast, robot-based assessments are objective, repeatable, and could potentially reduce the assessment time. However, robot-based assessments are not as well established as conventional assessment scale and the correlation to conventional assessment scale is unclear. OBJECTIVE This study was carried out to identify important parameters in designing tasks that efficiently assess hand function of stroke patients and to quantify potential benefits of robotic assessment modules to predict the conventional assessment score with iRest. METHODS Twelve predictive variables were explored, relating to movement time, velocity, strategy, accuracy and smoothness from three robotic assessment modules which are Draw I, Draw Diamond and Draw Circle. Regression models using up to four predictors were developed to describe the MAS. RESULTS Results show that the time given should be not too long and it would affect the trajectory error. Besides, result also shows that it is possible to use iRest in predicting MAS score. CONCLUSION There is a potential of using iRest, a non-motorized device in predicting MAS score.