-
Categories
-
Pharmaceutical Intermediates
-
Active Pharmaceutical Ingredients
-
Food Additives
- Industrial Coatings
- Agrochemicals
- Dyes and Pigments
- Surfactant
- Flavors and Fragrances
- Chemical Reagents
- Catalyst and Auxiliary
- Natural Products
- Inorganic Chemistry
-
Organic Chemistry
-
Biochemical Engineering
- Analytical Chemistry
-
Cosmetic Ingredient
- Water Treatment Chemical
-
Pharmaceutical Intermediates
Promotion
ECHEMI Mall
Wholesale
Weekly Price
Exhibition
News
-
Trade Service
Depression is the most common depressive disorder, with significant and lasting depression as the main clinical feature, and it is the main type of mood disorder
Depression is the most common depressive disorder, with significant and lasting depression as the main clinical feature, and it is the main type of mood disorder
A clear link between the effect of depression on the rehabilitation process and the functional recovery of patients has not yet been established
A clear link between the effect of depression on the rehabilitation process and the functional recovery of patients has not yet been established
The participant puts on the instrument and sits upright
The participant puts on the instrument and sits uprightThe study recruited 31 participants, including 14 adults (6 men and 8 women) with a clinical diagnosis of MDD and 17 healthy controls (6 men and 11 women)
The study recruited 31 participants, including 14 adults (6 men and 8 women) with a clinical diagnosis of MDD and 17 healthy controls (6 men and 11 women)
The continuous-wavelength fNIRS system (fNIRS equipment model 1000, USA) was used to record the light intensity emitted by 4 emitters and 10 detectors to obtain the hemodynamic response of 16 channels
fNIRS detection PFC activation sensitivity map
fNIRS detection PFC activation sensitivity mapThe study found that due to the number of features and the size of the data set used, the classification accuracy of the model is between 60% and 90%
The study found that due to the number of features and the size of the data set used, the classification accuracy of the model is between 60% and 90%
This study demonstrates the usefulness of predictive neurotechnology to classify depressive symptoms when performing motor tasks in adults
Y.
Leave a message here