Mechanical Engineering - Research Publications
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ItemPromoting clinical best practice in a user-centred design study of an upper limb rehabilitation robot(Taylor & Francis, 2021-01-01)Purpose: Despite their promise to increase therapy intensity in neurorehabilitation, robotic devices have not yet seen mainstream adoption. Whilst there are a number of contributing factors, it is obvious that the treating clinician should have a clear understanding of the objectives and limitations of robotic device use. This study sought to explore how devices can be developed to support a clinician in providing clinical best practice. Methods and Materials: A user-centred design study of a robotic device was conducted, involving build-then-use iterations, where successive iterations are built based on feedback from the use cycle. This work reports results of an analysis of qualitative and quantitative data describing the use of the robotic device in the clinical sessions, and from a focus group with the treating clinicians. Results and Conclusions: The data indicated that use of the device did not result in patient goal-setting and may have resulted in poor movement quality. Therapists expected a higher level of autonomy from the robotic device, and this may have contributed to the above problems. These problems can and should be addressed through modification of both the study design and device to provide more explicit instructions to promote clinical best practice. Implications for Rehabilitation: • Encouraging clinical best practice when using evaluating prototype devices within a clinical setting is important to ensure that best practice is maintained - and can be achieved through both study and device design • Support from device developers can significantly improve the confidence of therapists during the use of that device in rehabilitation, particularly with new or prototype devices • End effector-based robotic devices for rehabilitation show potential for a wide variety of patient presentations and capabilities.
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ItemEvaluating Rehabilitation Progress Using Motion Features Identified by Machine Learning(IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC, 2021-04)Evaluating progress throughout a patient's rehabilitation episode is critical for determining the effectiveness of the selected treatments and is an essential ingredient in personalised and evidence-based rehabilitation practice. The evaluation process is complex due to the inherently large human variations in motor recovery and the limitations of commonly used clinical measurement tools. Information recorded during a robot-assisted rehabilitation process can provide an effective means to continuously quantitatively assess movement performance and rehabilitation progress. However, selecting appropriate motion features for rehabilitation evaluation has always been challenging. This paper exploits unsupervised feature learning techniques to reduce the complexity of building the evaluation model of patients' progress. A new feature learning technique is developed to select the most significant features from a large amount of kinematic features measured from robotics, providing clinically useful information to health practitioners with reduction of modeling complexity. A novel indicator that uses monotonicity and trendability is proposed to evaluate kinematic features. The data used to develop the feature selection technique consist of kinematic data from robot-aided rehabilitation for a population of stroke patients. The selected kinematic features allow for human variations across a population of patients as well as over the sequence of rehabilitation sessions. The study is based on data records pertaining to 41 stroke patients using three different robot assisted exercises for upper limb rehabilitation. Consistent with the literature, the results indicate that features based on movement smoothness are the best measures among 17 kinematic features suitable to evaluate rehabilitation progress.
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ItemFlexible mechanical metamaterials enabling soft tactile sensors with multiple sensitivities at multiple force sensing ranges(NATURE PORTFOLIO, 2021-12-16)The majority of existing tactile sensors are designed to measure a particular range of force with a fixed sensitivity. However, some applications require tactile sensors with multiple task-relevant sensitivities at multiple ranges of force sensing. Inspired by the human tactile sensing capability, this paper proposes a novel soft tactile sensor based on mechanical metamaterials which exhibits multiple sensitivity regimes due to the step-by-step locking behaviour of its heterogenous multi-layered structure. By tuning the geometrical design parameters of the collapsible layers, each layer experiences locking behaviour under different ranges of force which provides different sensitivity of the sensor at different force magnitude. The integration of a magnetic-based transduction method with the proposed structure results in high design degrees of freedom for realising the desired contact force sensitivities and corresponding force sensing ranges. A systematic design procedure is proposed to select appropriate design parameters to produce the desired characteristics. Two example designs of the sensor structure were fabricated using widely available benchtop 3D printers and tested for their performance. The results showed the capability of the sensor in providing the desired characteristics in terms of sensitivity and force range and being realised in different shapes, sizes and number of layers in a single structure. The proposed multi-sensitivity soft tactile sensor has a great potential to be used in a wide variety of applications where different sensitivities of force measurement is required at different ranges of force magnitudes, from robotic manipulation and human-machine interaction to biomedical engineering and health-monitoring.
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ItemPsychometric Evaluation of Multi-Point Bone-Conducted Tactile Stimulation on the Three Bony Landmarks of the Elbow(IEEE, 2020)Sensory feedback is highly desirable in upper limb prostheses as well as in human robot interaction and other human machine interfaces. Bone conduction as sensory feedback interface is a recently studied approach showing promising properties. A combination of different feedback information is often necessary for prosthetic grasping, thus multiple feedback channels are required for effective sensory feedback. The use of multiple bone conduction stimulation sites simultaneously has not yet been studied. In this paper, the psychometric evaluation of multiple stimulation sites on the physiologically given bony landmarks on the elbow is investigated. The proposed approach is evaluated on human-subject experiments with six able-bodied subjects and one subject with transradial amputation. Vibrotactile transducers are placed on the bony landmarks of the elbow to determine the identification rate of each stimulation point separately as well as the identification rate of the number of active stimulation points for different frequencies. The outcomes show high identification rates for a frequency range from 100 to 750 Hz whilst performance deteriorates to at chance level at higher frequencies. A decreasing performance in identifying the number of active stimulation sites for an increasing number of simultaneous active transducers was observed. The obtained good performance in location identification suggests that information can be encoded via the location of the stimulation.
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ItemOn the Efficiency of Haptic Based Object Identification: Determining Where to Grasp to Get the Most Distinguishing Information(FRONTIERS MEDIA SA, 2021-07-29)Haptic perception is one of the key modalities in obtaining physical information of objects and in object identification. Most existing literature focused on improving the accuracy of identification algorithms with less attention paid to the efficiency. This work aims to investigate the efficiency of haptic object identification to reduce the number of grasps required to correctly identify an object out of a given object set. Thus, in a case where multiple grasps are required to characterise an object, the proposed algorithm seeks to determine where the next grasp should be on the object to obtain the most amount of distinguishing information. As such, the paper proposes the construction of the object description that preserves the association of the spatial information and the haptic information on the object. A clustering technique is employed both to construct the description of the object in a data set and for the identification process. An information gain (IG) based method is then employed to determine which pose would yield the most distinguishing information among the remaining possible candidates in the object set to improve the efficiency of the identification process. This proposed algorithm is validated experimentally. A Reflex TakkTile robotic hand with integrated joint displacement and tactile sensors is used to perform both the data collection for the dataset and the object identification procedure. The proposed IG approach was found to require a significantly lower number of grasps to identify the objects compared to a baseline approach where the decision was made by random choice of grasps.
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ItemCombining kinase inhibitors for optimally co-targeting cancer and drug escape by exploitation of drug target promiscuities.(Wiley, 2021-02)Cancers resist targeted therapeutics by drug-escape signaling. Multitarget drugs co-targeting cancer and drug-escape mediators (DEMs) are clinically advantageous. DEM coverage may be expanded by drug combinations. This work evaluated to what extent the kinase DEMs (KDEMs) can be optimally co-targeted by drug combinations based on target promiscuities of individual drugs. We focused on 41 approved and 28 clinical trial small molecule kinase inhibitor drugs with available experimental kinome and clinical pharmacokinetic data. From the kinome inhibitory profiles of these drugs, drug combinations were assembled for optimally co-targeting an established cancer target (EGFR, HER2, ABL1, or MEK1) and 9-16 target-associated KDEMs at comparable potency levels as that against the cancer target. Each set of two-, three-, and four-drug combinations co-target 36-71%, 44-89%, 50-88%, and 27-55% KDEMs of EGFR, HER2, ABL1, and MEK1, respectively, compared with the 36, 33, 38, and 18% KDEMs maximally co-targeted by an existing drug or drug combination approved or clinically tested for the respective cancer. Some co-targeted KDEMs are not covered by any existing drug or drug combination. Our work suggested that novel drug combinations may be constructed for optimally co-targeting cancer and drug escape by the exploitation of drug target promiscuities.
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ItemPoly(fluorenone-co-thiophene)-based nanoparticles for two-photon fluorescence imaging in living cells and tissues(ROYAL SOC CHEMISTRY, 2020-03-29)Conjugate polymer nanoparticles (CPNs) were constructed based on poly(fluorenone-co-thiophenes) (PFOTs) synthesized through a direct arylation polymerization (DArP) approach. Results demonstrate that the developed novel CPNs have potential applications in two-photon fluorescence imaging of both cells and tissues.
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ItemA biotin-guided hydrogen sulfide fluorescent probe and its application in living cell imaging.(Royal Society of Chemistry (RSC), 2020-09-28)Hydrogen sulfide (H2S), a well-known signaling molecule, exerts significant regulatory effects on the cardiovascular and nervous systems. Therefore, monitoring the metabolism of H2S offers a potential mechanism to detect various diseases. In addition, biotin is significantly used as a targeting group to detect cancer cells exclusively. In this work, a biotin-guided benzoxadizole-based fluorescent probe, NP-biotin, was developed for H2S detection and evaluated in normal liver cell (LO2) and liver cancer cell (HepG2) lines. Results reveal that NP-biotin can detect cellular H2S with high sensitivity and selectivity. Moreover, NP-biotin has been confirmed to possess the ability to target cancer cells under the guidance of the biotin group.
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ItemImproved Therapeutic Efficiency against Obesity through Transdermal Drug Delivery Using Microneedle Arrays.(MDPI AG, 2021-06-02)In this paper, we prepared patches that were composed of a degradable microneedle (MN) array with a soft backing provided for the skin tissue. We then performed a transdermal delivery of anti-obesity drugs to evaluate the effectiveness of β3 adrenergic receptor CL316243 in obesity treatment in overweight mice induced by a high-fat diet. Eighty male National Institutes of Health (NIH) mice were randomly divided into four obese groups or the control group. The obesity groups were given a high-fat diet for 15-18 weeks to establish an obese model. Afterward, the obese groups were divided into the following four groups: the control group, the unloaded MN group, the CL-316243 MN group, and the injection group. For the injection group, the group of mice was injected subcutaneously with CL316243 (1 mg/(kg·day)) for 15 days. Furthermore, the CL-316243 MN group was given a lower dose (0.1 mg/(kg·day)) for 15 days. After weighing the mice, we used Western blotting to detect the expression of uncoupling protein 1 (UCP1) in the adipose tissue around the mouse viscera. The results stated that the weight of the CL-316243 MN group and the injection group dropped, and the UCP1 protein expression of brown adipose tissue (BAT) significantly increased. The results demonstrated the β3 adrenergic receptor agonist CL316243 could be carried into the body through MN, and the dose applied was considerably smaller than the injection dose. The reason for this may arise from the CL-316243 being delivered by MN arrays to subcutaneous adipose tissue more efficiently, with an even distribution, compared to that of the injection dose. This technique provides a new and feasible way to treat obesity more effectively.
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