Inputs giving to Medical Robotic Services
Inputs giving to Medical Robotic Services
We help in giving inputs and suggestions to robotic approaches towards surgical aspects of treatment
Categories of Inputs for Medical Robotic Services
Human Inputs
These are the most direct and common types of inputs in robotic-assisted procedures.
| Input Type | Description |
|---|---|
| Manual Control | Surgeons use joysticks, consoles, or touchscreens to control robotic arms (e.g., in robotic surgery) |
| Voice Commands | Some robots respond to pre-programmed vocal instructions (used in rehabilitation and elder care) |
| Gesture Recognition | Advanced systems recognize hand or body gestures using cameras or wearables |
| Teleoperation | Remote surgeons control robotic systems in real time over the internet or private networks |
Sensor Inputs
Sensors provide environmental and physiological data, enabling robots to act safely and autonomously.
| Sensor Type | Purpose |
|---|---|
| Proximity Sensors | Detect nearby objects to prevent collisions |
| Pressure & Force Sensors | Help robots control grip or apply appropriate force during surgery or handling |
| Temperature Sensors | Monitor patient or instrument temperature (used in wound care, diagnostics) |
| Infrared & LIDAR | Map surroundings for navigation (e.g., hospital logistics robots) |
| Ultrasound Sensors | Aid in diagnostics or targeting during treatment |
| Haptic Feedback Systems | Provide tactile response to human operators, improving control in remote procedures |
| Vision Systems (Cameras) | Capture real-time visuals to guide robotic actions or assist in AI-based diagnostics |
Data and Software Inputs
Robots require complex programming and data feeds to operate accurately.
| Input Type | Role |
|---|---|
| Preoperative Medical Imaging | CT scans, MRI, and X-rays guide surgical navigation robots |
| Electronic Health Records (EHRs) | Provide context for patient-specific treatment or monitoring |
| AI Algorithms & Machine Learning Models | Used for predictive analytics, decision-making, and anomaly detection |
| Navigation Maps | Used by mobile robots for intra-hospital logistics (medicine delivery, disinfection) |
| Clinical Guidelines/Protocols | Embedded into software to ensure procedures follow regulatory and safety standards |
| Cloud-Based Data | Allows real-time updates, remote diagnostics, and collaborative interventions |
Biomedical Signals
These include real-time physiological readings from the patient.
| Signal | Use in Robotics |
|---|---|
| Electromyography (EMG) | Controls prosthetics or rehabilitation robots based on muscle activity |
| Electrocardiogram (ECG) | Used for monitoring and alert systems |
| Electroencephalography (EEG) | Used in brain-machine interfaces (BCIs) and robotic assistance for paralyzed patients |
| Respiratory and SpO₂ Data | Guide anesthetic or respiratory support robots |
| Blood Glucose/Pressure Monitors | Enable closed-loop insulin delivery or cardiac monitoring |
Environmental Inputs
These enable contextual awareness for robots working in hospitals or homes.
| Input | Function |
|---|---|
| Room Temperature & Humidity | Adjust operation of sterilization robots |
| Noise Levels | Used by conversational robots to adjust voice recognition sensitivity |
| Lighting Conditions | Affect camera-based navigation or facial recognition accuracy |
| Obstacle Detection | Guide autonomous hospital robots to navigate safely among staff and equipment |