There is no validated gold-standard diagnostic support tool for LSS, and therefore an accurate diagnosis depends on clinical assessment. Assessment of the diagnostic value of the history of the patient requires an evaluation of the differences and overlap of symptoms of the radicular and cauda equina types; however, no tool is available for evaluation of the LSS category. We attempted to develop a self-administered, self-reported history questionnaire as a diagnostic support tool for LSS using a clinical epidemiological approach. The aim of the present study was to use this tool to assess the diagnostic value of the history of the patient for categorization of LSS.

Functional electrical stimulation (FES) can improve the gait of stroke patients by stimulating the peroneal nerve in the swing phase of the affected leg, causing dorsiflexion of the foot that allows the toes to clear the ground. A sensor can trigger the electrical stimulation automatically during the stroke gait. We previously used a heel sensor system, which detects the contact pressure of the heel, in FES to correct foot drop gait. However, the heel sensor has disadvantages in cosmetics and durability. Therefore, we have replaced the heel sensor with an acceleration sensor that can detect the swing phase based on the acceleration speed of the affected leg, using a machine learning technique (Neural Network). We have used a signal for heel contact in a gait using the heel sensor before training with the Neural Network. The accuracy of the Neural Network detector was compared with a swing phase detector based on the heel sensor. The Neural Network detector was able to detect similarly the swing phase in the heel sensor. The largest difference in timing of the swing phase was less than 60 milliseconds in normal subjects and 80 milliseconds in stroke patients. We were able to correct foot drop gait using FES with an acceleration sensor and Neural Network detector. The present results indicate that an acceleration sensor positioned on the thigh, which is cosmetically preferable to systems in which the sensor is farther from the entry point of the electrodes, is useful for correction of stroke gait using FES.

In this study, we evaluated the clinical features of cauda equina tumors requiring surgical treatment. Medical records of 28 patients with cauda equina tumors (13 men and 15 women) undergoing surgical treatment were retrospectively reviewed. The majority of histological diagnoses indicated schwannoma (23 cases, 82%), and the remaining 5 indicated ependymoma, neurofibroma, meningioma, and ganglioneuroblastoma. In 86% of the cases, the initial symptom was pain in the lower back and/or lower extremities. Preoperatively, half of the patients had symmetrical pain in the lower back or lower extremities, severe pain in the supine position, or pain that was increased by coughing. One third of the patients needed morphine to control nocturnal pain. Tumor size, as determined by magnetic resonance imaging (MRI), correlated with preoperative symptom duration (r = 0.66, p < 0.001). These findings indicate that symmetrical lower back pain and/or pain that radiates to both lower extremities and increases in the supine position are characteristic of cauda equina tumors. The correlation between symptom duration and tumor size indicates that earlier diagnosis of this tumor is necessary. Earlier diagnosis based on these characteristic symptoms should make use of further examinations such as MRI.