Kouhei Ohnishi’s research while affiliated with Kanagawa Institute of Technology and other places

The sensation of the contact is indispensable for the contact task. In this chapter, the instantaneous value of the force/tactile sensation is defined and quantified as the ratio of the force and the velocity. The absolute value is also defined by the rms value with the definition of the time window. This value is extended to the frequency domain with the four parameters, which are also the admittance of the contact object. The operating point of the contact task in the force–velocity plane should be the crossing point of the characteristics of the actuation and the mechanical load. This is the same as the coincidence of the force/tactile sensation with the admittance of the contact object. Since the admittance of the contact object is varied according to the motion, such a coincidence should be maintained by the feedback mechanism. As a result, the feedforward system to define the mission of the contact and the feedback system for the matching the admittance is the essential structure of the contact task. That is shown by the figures and the experimental results.

The current methods to generate robot actions for automation in significantly different environments have limitations. This paper proposes a new method that matches the impedance of two prerecorded action data with the current environmental impedance to generate highly adaptable actions. This method recalculates the command values for the position and force based on the current impedance to improve reproducibility in different environments. Experiments conducted under conditions of extreme action impedance, such as position and force control, confirmed the superiority of the proposed method over existing motion reproduction system. The advantages of this method include the use of only two sets of motion data, significantly reducing the burden of data acquisition compared with machine-learning-based methods, and eliminating concerns about stability by using existing stable control systems. This study contributes to improving the environmental adaptability of robots while simplifying the action generation method.

The technology for generating robot actions has significantly contributed to the automation and efficiency of tasks. However, the ability to adapt to objects of different shapes and hardness remains a challenge for general industrial robots. Motion reproduction systems (MRS) replicate previously acquired actions using position and force control, but generating actions for significantly different environments is difficult. Furthermore, methods based on machine learning require the acquisition of a large amount of motion data. This paper proposes a new method that matches the impedance of two pre-recorded action data with the current environmental impedance to generate highly adaptable actions. This method recalculates the command values for position and force based on the current impedance to improve reproducibility in different environments. Experiments conducted under conditions of extreme action impedance, such as position control and force control, confirmed the superiority of the proposed method over MRS. The advantages of this method include using only two sets of motion data, significantly reducing the burden of data acquisition compared to machine learning-based methods, and eliminating concerns about stability by using existing stable control systems. This study contributes to improving robots' environmental adaptability while simplifying the action generation method.

The stiffness of human cancers may be corelated with their pathology, and can be used as a biomarker for diagnosis, malignancy prediction, molecular expression, and postoperative complications. Neurosurgeons perform tumor resection based on tactile sensations. However, it takes years of surgical experience to appropriately distinguish brain tumors from surrounding parenchymal tissue. Haptics is a technology related to the touch sensation. Haptic technology can amplify, transmit, record, and reproduce real sensations, and the physical properties (e.g., stiffness) of an object can be quantified. In the present study, glioblastoma (SF126-firefly luciferase-mCherry [FmC], U87-FmC, U251-FmC) and malignant meningioma (IOMM-Lee-FmC, HKBMM-FmC) cell lines were transplanted into nude mice, and the stiffness of tumors and normal brain tissues were measured using our newly developed surgical forceps equipped with haptic technology. We found that all five brain tumor tissues were stiffer than normal brain tissue (p<0.001), and that brain tumor pathology (three types of glioblastomas, two types of malignant meningioma) was significantly stiffer than normal brain tissue (p<0.001 for all). While glioblastomas showed no significant stiffness differences (p=0.468), IOMM-Lee-FmC was stiffer than HKBMM-FmC among meningiomas (p=0.032). Histologically, compared with IOMM-Lee-FmC, HKBMM-FmC showed abundant necrotic foci (i.e., similar to glioblastoma), which may explain the differences in stiffness.

BACKGROUND The stiffness of human cancers is correlated with their pathology, and can be used as a biomarker for diagnosis, malignancy prediction, molecular expression, and postoperative complications. Neurosurgeons perform tumor resection based on tactile sensations. However, it takes years of surgical experience to appropriately distinguish brain tumors from surrounding parenchymal tissue. Haptics is a technology that can amplify, transmit, record, and reproduce real tactile sensation, and the physical properties (e.g., stiffness) of an object can be quantified. METHODS glioblastoma (SF126-FmC, U87-FmC, U251-FmC) and malignant meningioma (IOMM-Lee-FmC, HKBMM-FmC) cell lines were transplanted into nude mice, and the stiffness of tumors and normal brain tissues were measured using our newly developed surgical forceps equipped with haptic technology (haptic forceps). Furthermore, pathological examination was performed to explore the correlation between stiffness and histological characteristics. RESULTS We found that all five brain tumor tissues were stiffer than normal brain tissue (p<0.001), and that brain tumor (three types of glioblastomas and two types of malignant meningioma) was significantly stiffer than normal brain tissue (p<0.001 for all). The stiffness among glioblastomas was not statistically significant (p=0.468) however, among the 2 malignant meningiomas, IOMM-Lee-FmC was significantly stiffer than HKBMM-FmC (p=0.032). Upon pathological examination, no significant differences were observed in the expression of collagen fibers. However, HKBMM-FmC demonstrated a higher prevalence of necrotic changes compared to IOMM-Lee-FmC. CONCLUSIONS Our findings suggest that tissue stiffness could be a marker not only to distinguish brain tumors from surrounding parenchymal tissue but also to distinguish pathology and malignancy of tumors. It is also suggested that the stiffness perceived during actual surgery and the stiffness quantified using haptic forceps may correlate with histological differences. Haptic forceps may help neurosurgeons to sense minute changes in tissue stiffness.

The stiffness of human cancers may be correlated with their pathology, and can be used as a biomarker for diagnosis, malignancy prediction, molecular expression, and postoperative complications. Neurosurgeons perform tumor resection based on tactile sensations. However, it takes years of surgical experience to appropriately distinguish brain tumors from surrounding parenchymal tissue. Haptics is a technology related to the touch sensation. Haptic technology can amplify, transmit, record, and reproduce real sensations, and the physical properties (e.g., stiffness) of an object can be quantified. In the present study, glioblastoma (SF126-firefly luciferase-mCherry [FmC], U87-FmC, U251-FmC) and malignant meningioma (IOMM-Lee-FmC, HKBMM-FmC) cell lines were transplanted into nude mice, and the stiffness of tumors and normal brain tissues were measured using our newly developed surgical forceps equipped with haptic technology. We found that all five brain tumor tissues were stiffer than normal brain tissue (p < 0.001), and that brain tumor pathology (three types of glioblastomas, two types of malignant meningioma) was significantly stiffer than normal brain tissue (p < 0.001 for all). Our findings suggest that tissue stiffness may be a useful marker to distinguish brain tumors from surrounding parenchymal tissue during microsurgery, and that haptic forceps may help neurosurgeons to sense minute changes in tissue stiffness.

Stiffness of human cancers strongly correlate with their pathology, and it is reported that stiffness can be used as a biomarker. Furthermore, comprehensive analysis has suggested the usefulness of cancer stiffness in diagnosis and malignancy prediction and its association with molecular expression, as well as its potential for predicting and diagnosing postoperative complications. Neurosurgeons perform tumor resection relying on the sensations that they feel with their own fingertips (tactile sensation), but it takes years of surgical experience to accurately distinguish brain tumor from the surrounding normal brain tissue. Haptics is a new technology regarding touching sensation. Especially, our technology, real haptics, can communicate, record, and reproduce the real sensation. It is also possible to measure and analyze the physical property such as stiffness of the touching object from the obtained haptic data. We developed a surgical forceps equipped with haptics technology to distinguish brain tumor tissue from surrounding normal brain tissue. three glioblastoma cell lines (SF126, U87, U251) and a malignant meningioma cell line (IOMM-Lee) were each transplanted intracranially into 5 nude mice. Tumor size was periodically monitored and mice were euthanized at appropriate time points. The stiffness of the tumor and normal brain tissue was measured using a master-slave integrated surgical forceps prototype. The results statistically showed that all four types of brain tumor tissues were stiffer than normal brain tissues. (p = 0.001) In addition, malignant meningioma was statistically stiffer than glioblastomas. (p = 0.025) This result is consistent with actual surgical sensations. We have shown that our surgical forceps has the ability to distinguish pathology of brain tumors as well as to distinguish brain tumor from normal brain tissue. The forceps is also helpful for the neurosurgeons to sense minute change in tissue stiffness.