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Powered prostheses are effective for helping amputees walk on level ground, but these devices are inconvenient to use in complex environments. Prostheses need to understand the motion intent of amputees to help them walk in complex environments. Recently, researchers have found that they can use vision sensors to classify environments and predict the motion intent of amputees. Previous researchers can classify environments accurately in the offline analysis, but they neglect to decrease the corresponding time delay. To increase the accuracy and decrease the time delay of environmental classification, we propose a new decision fusion method in this paper. We fuse sequential decisions of environmental classification by constructing a hidden Markov model and designing a transition probability matrix. We evaluate our method by inviting ablebodied subjects and amputees to implement indoor and outdoor experiments. Experimental results indicate that our method can classify environments more accurately and with less time delay than previous methods. Besides classifying environments, the proposed decision fusion method may also optimize sequential predictions of the human motion intent in the future.

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Background: Cancer causes a serious health burden on patients worldwide. Chronic low-level inflammation plays a key role in tumorigenesis and prognosis. However, the role of the red blood cell distribution width (RDW)-to-albumin (RA) ratio in cancer mortality remains unclear. Methods:In this retrospective cohort study, we collected clinical information from cancer patients from the Medical Information Mart for Intensive Care III (MIMIC-III) version 1.4 database and then calculated RA by dividing RDW by albumin concentration. The primary outcome was 30 days mortality, while secondary outcomes were 90 days and 1 year mortality. Next, we adopted Cox regression models to calculate hazard ratios (HR) together with 95% confidence intervals (CI) for all-cause mortalities associated with the RA ratio.Results: For 30 days mortality, the HR (95% CI) for the high RA ratio (≥5.51) was 2.17 [95CI% (1.87-2.51); p = <0.0001], compared with the low RA ratio (<5.51). In Model 2, we adjusted sex and age and obtained HR (95% CI) of 2.17 [95CI% (1.87-2.52); p = <0.0001] for the high RA ratio (≥5.51) group, compared to that in the low RA ratio (<5.51). In Model 3, adjusting for age, sex, anion gap, hematocrit, white blood cell count, congestive heart failure, SOFA, liver disease, and renal failure resulted in HR (95% CI) of 1. ; p = <0.0001] for the high RA ratio (≥5.51) relative to the low RA ratio (<5.51). We also analyzed common diseases in cancer patients but found no significant association. Conclusion:To the best of our knowledge, this is the first study demonstrating that increased RA ratio is independently associated with increased all-cause mortality in cancer patients.

The malignant transformation of abdominal wall endometriosis is a rare event and poorly understood. Less than 30 cases have been reported in the literature. Most of the reported cases have a solitary tumor in the abdominal scar. A few cases have metastasis. Here we report a case of clear cell carcinoma in abdominal wall endometriosis with bladder and lymph system metastasis. The patient had a history of abdominal wall endometriosis and recently developed symptoms of urgent urination and inguinal mass. Physical examination and a computed tomography (CT) scan detected lymph node metastasis. CT and cystoscopy confirmed bladder involvement. The patient underwent extensive surgery and chemotherapy. Pathological analysis made a diagnosis of clear cell carcinoma with bladder and lymph node metastasis. The patient was followed up and died of the disease. Symptoms of bladder invasion and lymph node spread could be a sign of malignant transformation. Local invasion and lymph node spread are two important forms of tumor metastasis. Extensive lymph nodes metastasis might be related with poor prognosis.