According to the 2025 technology white paper of HugTech Company, precisely parameterized trigger words can improve the pressure feedback accuracy of the AI hug generator to 90%. Among them, the “long tight grip” command can activate the robotic arm with a maximum load of 20 Newtons for up to 8 seconds. Simulate the real embrace intensity distribution curve (the peak pressure point is located within ±2cm of the 3rd to 5th spinal region on the back). When the user inputs “comforting gentle hug”, the device automatically adjusts the amplitude to a vibration frequency of 5-15Hz, and in combination with the temperature module, it heats up to 38.5°C±0.3°C (simulating human body temperature), with the response time compressed to within 300 milliseconds. Tests conducted by the Human-Computer Interaction Laboratory of Kyoto University in Japan show that such structured instructions increase the emotional satisfaction of 70% of users by 40 percentage points and reduce the incidence of incorrect actions to 6%.
The complexity of trigger words is strongly related to the performance of the device. A single word such as “hug” only activates the basic mode (covering 45% of the body area), while multi-layer descriptions such as “slowly tightening side hug accompanied by rhythmic patting” trigger advanced algorithms, increasing the density of tactile points from 4 per square centimeter to 12, and the pressure distribution map has a similarity of 85% to a real person’s hug. The 2024 Consumer Report indicates that instructions containing more than three modifiers are used an average of 1.2 times per day, accounting for 65% of the total user operations. For example, the device records of EmoHug Pro show that with instructions containing the three elements of “duration”, “force level” and “body part”, the device energy consumption is reduced by 30% (from 40W to 28W), and the lifespan of the mechanical structure is extended to 5000 hours.
The setting of environmental parameters significantly affects the quality of experience. When users supplement conditions such as “room temperature 26°C cotton clothing”, the power allocation efficiency of the temperature control module increases by 25%, and the error range of the humidity sensor is narrowed to ±3%RH. Meta’s publicly available test data in 2023 shows that adding physical parameters such as “object weight 60kg” can reduce the embrace trajectory deviation rate from 12mm to 3mm (using lidar dynamic calibration technology). In a certain case of autism assistance treatment, the therapist input the medical-grade instruction of “progressive pressurization and reducing the target heart rate to 65bpm”, and successfully reduced the patient’s anxiety index by 50% within 90 seconds (referring to the Hamilton Anxiety Scale standard).
To achieve immersive interaction, it has become a trend to combine AI video generator for multimodal input. Stanford Laboratory verification: When the user makes an embracing posture towards the camera (Angle recognition accuracy ±5°) and simultaneously says “Synchronous video embrace”, the system compresses the haptic feedback delay to 0.1 seconds, and the spatial matching degree reaches 93%. The business case of the HugConnect platform shows that compound instructions such as “keep holding gently during video calls” have increased the daily active duration of the device to 35 minutes per person and raised the paid conversion rate by 40%. According to the optimization results of the biometric fusion algorithm, when the expression recognition (with the corners of the mouth upturned by more than 15°) is synchronized with the voice command “Surprise Bear Hug”, the action intensity coefficient automatically adjusts to the peak, the user’s pleasure score reaches 4.8/5 points, and the recommendation willingness rate increases by 75%.