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With the progressive increase of stress, anxiety and depression in working and living environment, mental health assessment becomes an important social interaction research topic. Generally, clinicians evaluate the psychology of participants through an effective psychological evaluation and questionnaires. However, these methods suffer from subjectivity and memory effects. In this paper, a new multi-sensing wearable device has been developed and applied in self-designed psychological tests. Speech under different emotions as well as behavior signals are captured and analyzed. The mental state of the participants is objectively assessed through a group of psychological questionnaires. In particular, we propose an attention-based block deep learning architecture within the device for multi-feature classification and fusion analysis. This enables the deep learning architecture to autonomously train to obtain the optimum fusion weights of different domain features. The proposed attention-based architecture has led to improving performance compared with direct connecting fusion method. Experimental studies have been carried out in order to verify the effectiveness and robustness of the proposed architecture. The obtained results have shown that the wearable multi-sensing devices equipped with the attention-based block deep learning architecture can effectively classify mental state with better performance. INDEX TERMS Mental health assessment, wearable device, attention-based feature fusion.

The case we presented here was a 73-year-old gentleman, who was admitted to endocrinology department due to recurrent fatigue for 1 year. He had medical histories of type 2 diabetes for 18 years and developed CKD 4 years ago. He also suffered from dilated cardiomyopathy, and coronary heart disease, moderate sleep apnea syndrome, primary hypothyroidism, and gout. His treatment regimen was complicated which included Caltrate D and compound α-keto acid (1200 mg calcium/d). Laboratory examination revealed that his serum calcium level elevated, 24-hour urine calcium output decreased, PTH level was suppressed, and 25-hydroxyvitamin D was in normal low range. No other specific abnormalities were found in serum bone turnover markers, ultrasonography, computed tomography, and bone scintigraphy. The diagnosis was suggested to be hypocalciuric hypercalcemia but was different from familial or acquired hypocalciuric hypercalcemia which were featured by elevated PTH level. The patient was asked to restrict calcium intake and to take diuretics; then his serum calcium level gradually lowered. In brief, patients with CKD could present with hypocalciuric hypercalcemia due to impaired renal calcium excretion. In this case, calcium restriction should be applied for treatment.

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