Novel robotic systems and future directions

Development of a master-slave 3D printed robotic surgical finger with haptic feedback

Robotic surgery started nearly 30 years ago. It has achieved telepresence and the performance of repetitive, precise, and accurate tasks. The "master-slave" robotic system allows control of manipulators by surgeon at distant site. Robotic surgical fingers were developed to allow surgeons to move them with accuracy through sensors fixed on surgeon's hand. Also, haptic sensors were developed to allow transmission of sensation from robotic finger to surgeon's finger. A complete system of a, 3D printed by a stereolithography (SLA) 3D printer, robotic surgical finger with haptic feedback system is proposed. The developed system includes a master glove that controls the motion of a 3DOF robotic slave finger while getting haptic feedback of force/pressure exerted on it. The precise control of the slave robotic finger was achieved by applying a Proportional Integral and Derivative (PID), fast and robust, control algorithm using an Arduino based hardware and software module. The individual joint angles, metacarpophalangeal joint (MCP) and proximal interphalangeal joint (PIP), and wrist were measured using rotatory and inertial sensors respectively. The degree of movement for MCP, PIP, and Wrist joints were measured to be 0-86°, 0-71°, and 0-89° respectively. Motion to the robotic finger is mimicked by a glove motion requiring minimal learning curve for the device. The collected data for the slave motion is in good agreement with the master-glove motion data. The vibro-tactile haptic feedback system was developed to distinguish between three different materials to mimic human flesh, tumor, and bone. The master-slave system using robotic surgical finger with good simultaneous movement to surgeon's finger and good haptic sensation will provide the surgeon with the opportunity to perform finger dissection in laparoscopic and robotic surgery, as it used to be in open surgery. 3D bio printing will make this process even cheaper with the added advantage of making surgical tools locally according to the need of the surgery. An ongoing work is to develop silicone based 8 mm robotic surgical finger with multiple type haptic feedback.

Genomic insights into heart health: Exploring the genetic basis of cardiovascular disease

Cardiovascular diseases (CVDs) are considered as the leading cause of death worldwide. CVD continues to be a major cause of death and morbidity despite significant improvements in its detection and treatment. Therefore, it is strategically important to be able to precisely characterize an individual's sensitivity to certain illnesses. The discovery of genes linked to cardiovascular illnesses has benefited from linkage analysis and genome-wide association research. The last 20 years have seen significant advancements in the field of molecular genetics, particularly with the development of new tools like genome-wide association studies. In this article we explore the profound impact of genetic variations on disease development, prognosis, and therapeutic responses. And the significance of genetics in cardiovascular risk assessment and the ever-evolving realm of genetic testing, offering insights into the potential for personalized medicine in this domain. Embracing the future of cardiovascular care, the article explores the implications of pharmacogenomics for tailored treatments, the promise of emerging technologies in cardiovascular genetics and therapies, including the transformative influence of nanotechnology. Furthermore, it delves into the exciting frontiers of gene editing, such as CRISPR/Cas9, as a novel approach to combat cardiovascular diseases. And also explore the potential of stem cell therapy and regenerative medicine, providing a holistic view of the dynamic landscape of cardiovascular genomics and its transformative potential for the field of cardiovascular medicine.

Survey of Transfer Learning Approaches in the Machine Learning of Digital Health Sensing Data

Machine learning and digital health sensing data have led to numerous research achievements aimed at improving digital health technology. However, using machine learning in digital health poses challenges related to data availability, such as incomplete, unstructured, and fragmented data, as well as issues related to data privacy, security, and data format standardization. Furthermore, there is a risk of bias and discrimination in machine learning models. Thus, developing an accurate prediction model from scratch can be an expensive and complicated task that often requires extensive experiments and complex computations. Transfer learning methods have emerged as a feasible solution to address these issues by transferring knowledge from a previously trained task to develop high-performance prediction models for a new task. This survey paper provides a comprehensive study of the effectiveness of transfer learning for digital health applications to enhance the accuracy and efficiency of diagnoses and prognoses, as well as to improve healthcare services. The first part of this survey paper presents and discusses the most common digital health sensing technologies as valuable data resources for machine learning applications, including transfer learning. The second part discusses the meaning of transfer learning, clarifying the categories and types of knowledge transfer. It also explains transfer learning methods and strategies, and their role in addressing the challenges in developing accurate machine learning models, specifically on digital health sensing data. These methods include feature extraction, fine-tuning, domain adaptation, multitask learning, federated learning, and few-/single-/zero-shot learning. This survey paper highlights the key features of each transfer learning method and strategy, and discusses the limitations and challenges of using transfer learning for digital health applications. Overall, this paper is a comprehensive survey of transfer learning methods on digital health sensing data which aims to inspire researchers to gain knowledge of transfer learning approaches and their applications in digital health, enhance the current transfer learning approaches in digital health, develop new transfer learning strategies to overcome the current limitations, and apply them to a variety of digital health technologies.

Robot-Assisted versus Laparoscopic Gastrointestinal Surgery: A Systematic Review and Metanalysis of Intra- and Post-Operative Complications

BACKGROUND

The use of robotic surgery is attracting ever-growing interest for its potential advantages such as small incisions, fine movements, and magnification of the operating field. Only a few randomized controlled trials (RCTs) have explored the differences in perioperative outcomes between the two approaches.

METHODS

We screened the main online databases from inception to May 2023. We included studies in English enrolling adult patients undergoing elective gastrointestinal surgery. We used the following exclusion criteria: surgery with the involvement of thoracic esophagus, and patients affected by severe heart, pulmonary and end-stage renal disease. We compared intra- and post-operative complications, length of hospitalization, and costs between laparoscopic and robotic approaches.

RESULTS

A total of 18 RCTs were included. We found no differences in the rate of anastomotic leakage, cardiovascular complications, estimated blood loss, readmission, deep vein thrombosis, length of hospitalization, mortality, and post-operative pain between robotic and laparoscopic surgery; post-operative pneumonia was less frequent in the robotic approach. The conversion to open surgery was less frequent in the robotic approach, which was characterized by shorter time to first flatus but higher operative time and costs.

CONCLUSIONS

The robotic gastrointestinal surgery has some advantages compared to the laparoscopic technique such as lower conversion rate, faster recovery of bowel movement, but it has higher economic costs.

Revo-i assisted robotic central pancreatectomy

Central pncreatectomy (CP) can be one of procedures for function-preserving pancreatectomy for patients with benign or low grade malignant pancreatic tumors. Surgeons have to deal with two cut surface of the pancreas when performing CP, which can be associated with severe complication, such as postoperative pancreatic fistula. Fine and delicate surgical skill is highly required for safe CP. With the advance of minimally invasive surgery, CP is now thought to be one of appropriate procedures for function-preserving minimally invasive pancreatectomy. Robotic surgery is thought to make complicated surgical procedure easy and effective. Recently, Korean robotic surgical system, Revo-i, was successfully developed by Meeraecompany and have been proved its safety and feasibility in several recent reports. A 56-year old woman was referred for a body of pancreatic lesion. Contrast abdominopelvic CT revealed a pancreatic body tumor measuring around 1.2 cm in diameter. The patient underwent a robot-assisted central pancreatectomy using Revo-i. The patient endured the procedure well and was discharged to home at postoperative day 9. This report showed a successful case of central pancreatectomy performed with the Korean robotic surgical system Revo-i.

Laparoscopic Robotic Surgery: Current Perspective and Future Directions

Just as laparoscopic surgery provided a giant leap in safety and recovery for patients over open surgery methods, robotic-assisted surgery (RAS) is doing the same to laparoscopic surgery. The first laparoscopic-RAS systems to be commercialized were the Intuitive Surgical, Inc. (Sunnyvale, CA, USA) da Vinci and the Computer Motion Zeus. These systems were similar in many aspects, which led to a patent dispute between the two companies. Before the dispute was settled in court, Intuitive Surgical bought Computer Motion, and thus owned critical patents for laparoscopic-RAS. Recently, the patents held by Intuitive Surgical have begun to expire, leading to many new laparoscopic-RAS systems being developed and entering the market. In this study, we review the newly commercialized and prototype laparoscopic-RAS systems. We compare the features of the imaging and display technology, surgeons console and patient cart of the reviewed RAS systems. We also briefly discuss the future directions of laparoscopic-RAS surgery. With new laparoscopic-RAS systems now commercially available we should see RAS being adopted more widely in surgical interventions and costs of procedures using RAS to decrease in the near future.

Nanotechnology, an alternative with promising prospects and advantages for the treatment of cardiovascular diseases

Cardiovascular diseases (CVDs) are one of the most important causes of mortality and affecting the health status of patients. At the same time, CVDs cause a huge health and economic burden to the whole world. Although a variety of therapeutic drugs and measures have been produced to delay the progress of the disease and improve the quality of life of patients, most of the traditional therapeutic strategies can only cure the symptoms and cannot repair or regenerate the damaged ischemic myocardium. In addition, they may bring some unpleasant side effects. Therefore, it is vital to find and explore new technologies and drugs to solve the shortcomings of conventional treatments. Nanotechnology is a new way of using and manipulating the matter at the molecular scale, whose functional organization is measured in nanometers. Because nanoscale phenomena play an important role in cell signal transduction, enzyme action and cell cycle, nanotechnology is closely related to medical research. The application of nanotechnology in the field of medicine provides an alternative and novel direction for the treatment of CVDs, and shows excellent performance in the field of targeted drug therapy and the development of biomaterials. This review will briefly introduce the latest applications of nanotechnology in the diagnosis and treatment of common CVDs.