Bruns Nystagmus in Cerebellopontine Angle Hemangioblastoma.

Bruns nystagmus is a form of jerk nystagmus that has a localizing value in cerebellopontine angle (CPA) tumors. Hemangioblastomas involving the CPA is rare. A case of a 57-year-old male presented with Bruns nystagmus which led to the discovery of a large CPA hemangioblastoma is described. The nystagmus was compatible with the laterality of the tumor. High quality video of Bruns nystagmus was recorded.

Narrow-band imaging for detecting nasal lymphoma.

INTRODUCTION: Narrow-band imaging (NBI) is an advanced endoscopic technique that enhances the mucosal neovascularization. The utilization of narrow-band imaging on the detection of nasal lymphomas is not well-established. AIM: To present a clinical case whose nasal lymphoma was detected with the aid of NBI. CASE REPORT: A 91-year-old male presented to the ear, nose, and throat clinic with right persisting nasal obstruction for 4 months. NBI revealed a well demarcated lesion with an elongated vessel on the surface of the right inferior nasal turbinate. Histopathologic analysis of tissue specimen proved to be extranodal NK/T-cell lymphoma, nasal type. CONCLUSIONS: NBI is useful for the detection of nasal lymphomas. NBI may be a valuable screening tool for nasal lymphomas as it is non-invasive and affordable.

Acute sensorineural hearing loss in hemodialysis patients.

Background: Approximately, 30-40% of patients experienced hearing loss under regular hemodialysis.Objective: This study reviewed our experience on treating acute hearing loss in patients under regular hemodialysis over the past two decades.Methods: Twenty-six patients having acute hearing loss under hemodialysis were divided into two groups based on their etiologies. Sixteen patients (16 ears) with sudden sensorineural hearing loss (SSHL) were assigned to Group A and 10 patients (13 ears) with endolymphatic hydrops (EH) were assigned to Group B.Results: No significant difference was noted between Groups A and B, regardless of hemodialysis duration, clinical manifestation, underlying systemic diseases, blood examination, and vestibular test battery. In contrast, serum osmolality was significantly lower in Group B (292 ± 11 mOsm/kg) than in Group A (310 ± 11 mOsm/kg). Furthermore, Group B (40 ± 14 dB) had better mean hearing level than Group A (87 ± 21 dB) in the initial audiogram, and a higher hearing improvement rate (69%) than Group A (19%).Conclusions and significance: Both SSHL and EH are major causes for precipitating acute hearing loss in hemodialysis patients. Compared to SSHL, the less deteriorated MHL and lower serum osmolality in EH provide two clues for differentiating acute hearing loss in hemodialysis patients.

Sleeping posture recognition using fuzzy c-means algorithm.

BACKGROUND: Pressure sensors have been used for sleeping posture detection, which meet privacy requirements. Most of the existing techniques for sleeping posture recognition used force-sensitive resistor (FSR) sensors. However, lower limbs cannot be recognized accurately unless thousands of sensors are deployed on the bedsheet. METHOD: We designed a sleeping posture recognition scheme in which FSR sensors were deployed on the upper part of the bedsheet to record the pressure distribution of the upper body. In addition, an infrared array sensor was deployed to collect data for the lower body. Posture recognition was performed using a fuzzy c-means clustering algorithm. Six types of sleeping body posture were recognized from the combination of the upper and lower body postures. RESULTS: The experimental results showed that the proposed method achieved an accuracy of above 88%. Moreover, the proposed scheme is cost-efficient and easy to deploy. CONCLUSIONS: The proposed sleeping posture recognition system can be used for pressure ulcer prevention and sleep quality assessment. Compared to wearable sensors and cameras, FSR sensors and infrared array sensors are unobstructed and meet privacy requirements. Moreover, the proposed method provides a cost-effective solution for the recognition of sleeping posture.

Body posture recognition and turning recording system for the care of bed bound patients.

This paper proposes body posture recognition and turning recording system for assisting the care of bed bound patients in nursing homes. The system continuously detects the patient's body posture and records the length of time for each body posture. If the patient remains in the same body posture long enough to develop pressure ulcers, the system notifies caregivers to change the patient's body posture. The objective of recording is to provide the log of body turning for querying of patients' family members. In order to accurately detect patient's body posture, we developed a novel pressure sensing pad which contains force sensing resistor sensors. Based on the proposed pressure sensing pad, we developed a bed posture recognition module which includes a bed posture recognition algorithm. The algorithm is based on fuzzy theory. The body posture recognition algorithm can detect the patient's bed posture whether it is right lateral decubitus, left lateral decubitus, or supine. The detected information of patient's body posture can be then transmitted to the server of healthcare center by the communication module to perform the functions of recording and notification. Experimental results showed that the average posture recognition accuracy for our proposed module is 92%.