Update README.md

README.md

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 **TinyMyo** is a **3.6M-parameter** Transformer-based **foundation model for surface EMG (sEMG)**.
-It is pretrained on >480 GB of EMG data and optimized for **ultra-low-power, real-time deployment**, including **microcontrollers (GAP9)** where it achieves **36.45 mW** average power consumption—the *first demonstration of an EMG foundation model running on an MCU*.
+It is pretrained on >480 GB of EMG data and optimized for **ultra-low-power, real-time deployment**, including **microcontrollers (GAP9)** where it achieves an inference time of **0.785 s**, energy of **44.91 mJ** and power envelope of **57.18 mW**.
 
 TinyMyo is built for **broad generalization** across datasets, sensor configurations, movement tasks, subjects, and domains (gesture, kinematics, speech).
 
@@ -356,9 +356,9 @@ TinyMyo runs efficiently on **GAP9 (RISC-V)** via:
 
 ### Runtime (DB5 pipeline)
 
-* **Inference time:** 12.2 s
-* **Energy:** 0.44 J
-* **Average power:** **36.45 mW**
+* **Inference time:** 0.785 s
+* **Energy:** 44.91 mJ
+* **Average power:** **57.18 mW**
 
 This is the **first EMG foundation model demonstrated on a microcontroller**.