Cable-driven parallel mechanisms for minimally invasive robotic surgery

Minimally invasive surgery (MIS) has revolutionised surgery by providing faster recovery times, less post-operative complications, improved cosmesis and reduced pain for the patient. Surgical robotics are used to further decrease the invasiveness of procedures, by using yet smaller and fewer incisions or using natural orifices as entry point. However, many robotic systems still suffer from technical challenges such as sufficient instrument dexterity and payloads, leading to limited adoption in clinical practice. Cable-driven parallel mechanisms (CDPMs) have unique properties, which can be used to overcome existing challenges in surgical robotics. These beneficial properties include high end-effector payloads, efficient force transmission and a large configurable instrument workspace. However, the use of CDPMs in MIS is largely unexplored. This research presents the first structured exploration of CDPMs for MIS and demonstrates the potential of this type of mechanism through the development of multiple prototypes: the ESD CYCLOPS, CDAQS, SIMPLE, neuroCYCLOPS and microCYCLOPS. One key challenge for MIS is the access method used to introduce CDPMs into the body. Three different access methods are presented by the prototypes. By focusing on the minimally invasive access method in which CDPMs are introduced into the body, the thesis provides a framework, which can be used by researchers, engineers and clinicians to identify future opportunities of CDPMs in MIS. Additionally, through user studies and pre-clinical studies, these prototypes demonstrate that this type of mechanism has several key advantages for surgical applications in which haptic feedback, safe automation or a high payload are required. These advantages, combined with the different access methods, demonstrate that CDPMs can have a key role in the advancement of MIS technology.Open Acces

The evaluation of a novel haptic machining VR-based process planning system using an original process planning usability method

This thesis provides an original piece of work and contribution to knowledge by creating a new process planning system; Haptic Aided Process Planning (HAPP). This system is based on the combination of haptics and virtual reality (VR). HAPP creates a simulative machining environment where Process plans are automatically generated from the real time logging of a user’s interaction. Further, through the application of a novel usability test methodology, a deeper study of how this approach compares to conventional process planning was undertaken. An abductive research approach was selected and an iterative and incremental development methodology chosen. Three development cycles were undertaken with evaluation studies carried out at the end of each. Each study, the pre-pilot, pilot and industrial, identified progressive refinements to both the usability of HAPP and the usability evaluation method itself. HAPP provided process planners with an environment similar to which they are already familiar. Visual images were used to represent tools and material whilst a haptic interface enabled their movement and positioning by an operator in a manner comparable to their native setting. In this way an intuitive interface was developed that allowed users to plan the machining of parts consisting of features that can be machined on a pillar drill, 21/2D axis milling machine or centre lathe. The planning activities included single or multiple set ups, fixturing and sequencing of cutting operations. The logged information was parsed and output to a process plan including route sheets, operation sheets, tool lists and costing information, in a human readable format. The system evaluation revealed that HAPP, from an expert planners perspective is perceived to be 70% more satisfying to use, 66% more efficient in completing process plans, primarily due to the reduced cognitive load, is more effective producing a higher quality output of information and is 20% more learnable than a traditional process planning approach

Smartphone Based Personalized Balance Training Platform

ME450 Capstone Design and Manufacturing Experience: Winter 2021Older adults are at high risk of falls, mainly due to the loss of balance control. It is important for them to regain balance control through balance training exercises for quality living. These exercises are conventionally done in a clinic-based setting under the supervision of a physical therapist (PT). However, this method comes with limitations such as cost, insurance reimbursement policies, and travel. Thus, there is a need for a portable balance training platform that can be used by older adults at home. Our team is developing a platform as such that can not only provide balance training to our users but can also measure kinematic data from multiple body parts and capture self-performance ratings after exercises are performed - these data are uploaded to a secure cloud account. The platform can also support a machine learning framework that generates a list of recommended exercises and simulated PT ratings for the users based on their performance during the balance training exercise sessions.Jamie Ferris, Safa Jabri, Christopher DiCesare, Xun Huan: Sienko Research Grouphttp://deepblue.lib.umich.edu/bitstream/2027.42/167652/1/Team_8-Smartphone_Based_Personalized_Balance_Training_Platform.pd

Low-Cost Sensors and Biological Signals

Many sensors are currently available at prices lower than USD 100 and cover a wide range of biological signals: motion, muscle activity, heart rate, etc. Such low-cost sensors have metrological features allowing them to be used in everyday life and clinical applications, where gold-standard material is both too expensive and time-consuming to be used. The selected papers present current applications of low-cost sensors in domains such as physiotherapy, rehabilitation, and affective technologies. The results cover various aspects of low-cost sensor technology from hardware design to software optimization

Developing a strategic controller with haptic and audio feedback for autonomous driving

Traffic accidents cause over 1.2 million deaths, and tens of millions of people are injured or disabled every year. Advanced driver assistant systems and other safety features have the possibility to reduce traffic accidents but do not account for human errors. Studies show that over 90% of all traffic accidents are caused by human errors. One way to reduce human errors is to introduce automation, and several major car manufacturers predict that autonomous vehicles will be available on the consumer marker as early as 2020. In theory automated cars could reduce deaths and injuries caused by traffic accidents, but there are several issues which need to be solved before it can be realized. One of these issues is how to keep the driver in the loop while the car is in autonomous mode. A human-machine interface of a strategic controller for autonomous driving was developed. Multimodal feedback consisting of auditory and haptic signals was developed for the strategic controller using an iterative design process. A user study was carried out in order to evaluate the multimodal feedback and identify usability issues, and a simulator study was carried out in order to benchmark the concept’s usability. The strategic controller prototype developed in this thesis allows the driver to take part of the driving process and control of the car by inputting commands. The controller also provides the driver with multimodal feedback based on an analysis of mock-up sensor/image data from the vehicle. User input is either denied or accepted depending on the analysed data, and on demand feedback is also provided related to the general state of the autonomous system. Multimodal feedback was found to be promising for communicating complex information in humanmachine interactions. Although users had little to no experience of autonomous driving, they found the developed concept to be attractive and would use it for daily commuting. As it is difficult to mirror reality in simulators, test subjects may have had a more positive attitude towards the concept. However, the issue of keeping the user in the loop still persists. Feedback needs to be designed thoroughly and should not be limited to two modalities. Instead, information should be distributed through several modalities in order to reduce cognitive load and increase the user’s situational awareness. The benchmark of the developed concept showed promising results, although the results may have suffered due to hardware limitations

Shared Control for Wheelchair Interfaces

Independent mobility is fundamental to the quality of life of people with impairment. Most people with severe mobility impairments, whether congenital, e.g., from cerebral palsy, or acquired, e.g., from spinal cord injury, are prescribed a wheelchair. A small yet significant number of people are unable to use a typical powered wheelchair controlled with a joystick. Instead, some of these people require alternative interfaces such as a head- array or Sip/Puff switch to drive their powered wheelchairs. However, these alternative interfaces do not work for everyone and often cause frustration, fatigue and collisions. This thesis develops a novel technique to help improve the usability of some of these alternative interfaces, in particular, the head-array and Sip/Puff switch. Control is shared between a powered wheelchair user, using an alternative interface and a pow- ered wheelchair fitted with sensors. This shared control then produces a resulting motion that is close to what the user desires to do but a motion that is also safe. A path planning algorithm on the wheelchair is implemented using techniques in mo- bile robotics. Afterwards, the output of the path planning algorithm and the user’s com- mand are both modelled as random variables. These random variables are then blended in a joint probability distribution where the final velocity to the wheelchair is the one that maximises the joint probability distribution. The performance of the probabilistic approach to blending the user’s inputs with the output of a path planner, is benchmarked against the most common form of shared control called linear blending. The benchmarking consists of several experiments with end users both in a simulated world and in the real-world. The thesis concludes that probabilistic shared control provides safer motion compared with the traditional shared control for difficult tasks and hard-to-use interfaces

Augmenting patient therapies with video game technology

PhD ThesisThere is an increasing body of work showing that video games can be used for more than just entertainment, but can also facilitate positive physical and mental changes. For people suffering debilitating side-effects from illnesses such as stroke, there is need to deliver and monitor effective rehabilitative physical therapies; video game technologies could potentially deliver an effective alternative to traditional rehabilitative physical therapy, and alleviate the need for direct therapist oversight. Most existing research into video game therapies has focussed on the use of offthe- shelf games to augment a patient’s ongoing therapy. There has currently been little progress into how best to design bespoke software capable of integrating with traditional therapy, or how to replicate common therapies and medical measurements in software. This thesis investigates the ability for video games to be applied to stroke rehabilitation, using modern gaming peripherals for input. The work presents a quantitative measurement of motion detection quality afforded by such hardware. An extendible game development framework capable of high quality movement data output is also presented, affording detailed analysis of player responsiveness to a video game delivered therapy for acute stroke. Finally, a system by which therapists can interactively create complex physical movements for their patients to replicate in a video game environment is detailed, enabling bespoke therapies to be developed, and providing the means by which rehabilitative games for stroke can provide an assessment of patient ability similar to that afforded by traditional therapies

磁性流体を用いたバックドライブ可能な油圧アクチュエータの開発

早大学位記番号:新7478早稲田大

Advanced Mobile Robotics: Volume 3

Mobile robotics is a challenging field with great potential. It covers disciplines including electrical engineering, mechanical engineering, computer science, cognitive science, and social science. It is essential to the design of automated robots, in combination with artificial intelligence, vision, and sensor technologies. Mobile robots are widely used for surveillance, guidance, transportation and entertainment tasks, as well as medical applications. This Special Issue intends to concentrate on recent developments concerning mobile robots and the research surrounding them to enhance studies on the fundamental problems observed in the robots. Various multidisciplinary approaches and integrative contributions including navigation, learning and adaptation, networked system, biologically inspired robots and cognitive methods are welcome contributions to this Special Issue, both from a research and an application perspective