“…In [45] there are two approaches to minimize thermal damage during bone drilling. The first strategy involves employing a higher feed rate to decrease the duration of the drilling process.…”
In orthopedics, bone drilling is a crucial part of a surgical method commonly carried out for internal fixation in bone fracture treatment. The primary purpose of bone drilling is the creation of holes for screw insertion to immobilize fractured parts. The bone drilling task depends on the orthopedist and surgeon’s high level of skill and experience. This paper aimed to provide a summary of previously published review studies in the field of bone drilling. This review paper also presents a comprehensive review of the application of machine learning for bone drilling and as a future direction for the automation system. This review can also help medical surgeons and bone drillers understand the latest improvements through parameter selection and optimization strategies to reduce bone damage in bone drilling procedures. Apart from the review study, bone drilling vibration data collected in the University laboratory experiment is also presented in this study. The vibration data consist of three different layers of femur cow bone which are processed and classified using several machine learning methods. LSTM is, used in the bone drilling classification study to prove that the layers of the bone drilling are associated with the vibration signal and can be classified and predicted using the machine learning method.
“…In [45] there are two approaches to minimize thermal damage during bone drilling. The first strategy involves employing a higher feed rate to decrease the duration of the drilling process.…”
In orthopedics, bone drilling is a crucial part of a surgical method commonly carried out for internal fixation in bone fracture treatment. The primary purpose of bone drilling is the creation of holes for screw insertion to immobilize fractured parts. The bone drilling task depends on the orthopedist and surgeon’s high level of skill and experience. This paper aimed to provide a summary of previously published review studies in the field of bone drilling. This review paper also presents a comprehensive review of the application of machine learning for bone drilling and as a future direction for the automation system. This review can also help medical surgeons and bone drillers understand the latest improvements through parameter selection and optimization strategies to reduce bone damage in bone drilling procedures. Apart from the review study, bone drilling vibration data collected in the University laboratory experiment is also presented in this study. The vibration data consist of three different layers of femur cow bone which are processed and classified using several machine learning methods. LSTM is, used in the bone drilling classification study to prove that the layers of the bone drilling are associated with the vibration signal and can be classified and predicted using the machine learning method.
“…The K-wire was small, and a small retractor was used to block the soft tissue, nerves and blood vessels, providing su cient space for drilling and osteotomy without stretching the soft tissue excessively. In addition, K-wire single drilling caused less thermal damage than midget electrosaw drilling [27]. Before the next drilling, fully rinsing with water was necessary for cooling.…”
Background
The treatment of hallux valgus has become increasingly minimally invasive. Following the framework of three generations of minimally invasive hallux valgus techniques, we designed the minimally invasive K-wire osteotomy (MIK) technique. We aimed to compare the radiological outcomes and clinical efficacy of the MIK technique with those of open surgery and to evaluate its clinical value.
Methods
In this retrospective study, we analyzed the data of patients who underwent hallux valgus surgery from July 2018 to July 2021. Patients were divided into the MIK and open groups according to the surgical method. Perioperative data, radiographicmeasurements of the hallux valgus angle (HVA) and intermetatarsal angle (IMA), American Orthopaedic Foot and Ankle Society Hallux Metatarsophalangeal-Interphalangeal Scale (AOFAS) scores, and visual analog scale (VAS) scores to assess efficacy were recorded.
Results
Seventy patients (72 feet) with hallux valgus were enrolled in this study, including 36 patients (38 feet) in the MIK group and 34 patients (34 feet) in the open group. The operation time and hospital stay were shorter in the MIK group than in the open group (P﹤0.05). No significant differences were observed in the HVA and IMA between the two groups at 6 weeks post-surgery and at the last follow-up (P﹥0.05). Six weeks post-operatively, the AOFAS and VAS scores of the MIK group were better than those of the open group (P﹤0.05). At the last follow-up, no significant difference was observed in the AOFAS and VAS scores between the two groups (P﹥0.05). The internal fixation was removed in one case in the MIK group and in two cases in the open group due to screw protrusion and skin irritation. No cases of wound infection, deformity recurrence, hallux varus, or metastatic metatarsalgia were observed in the two groups.
Conclusion
The MIK technique demonstrates comparable radiographic results and clinical efficacy to open surgery. It saves operation time and results in less trauma, less pain, faster functional recovery, and improved aesthetics. This technique does not require specialized equipment, making it suitable for application in most hospitals.
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