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What are the latest trends and innovations in AI for biomechatronics and prosthetics?

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Biomechatronics is a branch of mechatronics that combines mechanical, electronic, and computer engineering with biology to create devices that interact with living organisms. Prosthetics are artificial limbs or organs that replace or enhance the function of missing or damaged body parts. AI, or artificial intelligence, is the ability of machines or software to perform tasks that normally require human intelligence, such as learning, reasoning, and decision making. In this article, you will learn about some of the latest trends and innovations in AI for biomechatronics and prosthetics, and how they can improve the quality of life for people with disabilities or injuries.

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Dr. Daher Sayfeddine

Ph.D. (Robotics), D.Cert. CMI LEVEL 8, MEng.(Mechatronics & Int. Engineering), CMgr. FCMI, CEng MIET, PMP?, PRINCE2?…
Dharunkumar Senthilkumar

| Machine Learning, Robotics and Control | MSc MPSYS at Chalmers University |

1 AI-powered sensors

One of the key challenges in biomechatronics and prosthetics is to create devices that can sense and respond to the user's intentions, feedback, and environment. AI-powered sensors can help achieve this by using machine learning algorithms to process and interpret signals from various sources, such as nerves, muscles, skin, or cameras. For example, some prosthetic hands can use AI to detect the user's muscle activity and movement patterns, and adjust the grip and force accordingly. Some prosthetic legs can use AI to monitor the user's gait and terrain, and adapt the stiffness and damping of the joints. AI-powered sensors can also provide haptic feedback to the user, such as vibrations, pressure, or temperature, to simulate the sensation of touch.

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Dr. Daher Sayfeddine

Ph.D. (Robotics), D.Cert. CMI LEVEL 8, MEng.(Mechatronics & Int. Engineering), CMgr. FCMI, CEng MIET, PMP?, PRINCE2?, PMI-ACP?, PM LEVEL 6, PSM I?
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Integrating AI to provide sensory feedback to amputees is an area of active research. This involves developing systems that can transmit tactile sensations or proprioceptive feedback from the prosthetic limb to the user, enhancing their sense of touch and control.

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Dharunkumar Senthilkumar

| Machine Learning, Robotics and Control | MSc MPSYS at Chalmers University |
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Emotion Recognition: AI algorithms can be trained to recognize emotional states through physiological signals, allowing prosthetic devices to adapt their behavior based on the user's emotional context. Environmental Interaction: AI-enabled sensors can interpret environmental cues, helping prosthetics adjust their function in response to changes in surroundings, improving safety and user experience.

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2 AI-enabled communication

Another challenge in biomechatronics and prosthetics is to enable communication between the user and the device, as well as between different devices. AI-enabled communication can help overcome this by using natural language processing, speech recognition, and computer vision to facilitate verbal and non-verbal interactions. For example, some prosthetic arms can use AI to recognize voice commands and gestures, and execute different actions or modes. Some prosthetic eyes can use AI to convert visual information into auditory or tactile signals, and vice versa. AI-enabled communication can also allow the user to control multiple devices with a single interface, or to share data and feedback with other users or professionals.

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Dharunkumar Senthilkumar

| Machine Learning, Robotics and Control | MSc MPSYS at Chalmers University |
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Emotive Communication: AI can enhance communication by incorporating emotion detection, enabling prosthetics to convey emotions through subtle movements or expressions. Predictive Speech Synthesis: AI-driven predictive models can improve the accuracy and speed of speech synthesis for users relying on prosthetic speech interfaces.

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3 AI-based design and customization

A third challenge in biomechatronics and prosthetics is to design and customize devices that fit the user's needs, preferences, and anatomy. AI-based design and customization can help solve this by using generative design, computer-aided design, and additive manufacturing to create optimal and personalized solutions. For example, some prosthetic sockets can use AI to generate 3D models based on the user's measurements, shape, and biomechanics, and print them using flexible materials. Some prosthetic skins can use AI to match the user's skin tone, texture, and appearance, and print them using biocompatible materials. AI-based design and customization can also enable the user to modify and update their devices according to their changing conditions or goals.

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Dharunkumar Senthilkumar

| Machine Learning, Robotics and Control | MSc MPSYS at Chalmers University |
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Adaptive Proactive Assistance: AI algorithms can anticipate user intent and provide proactive assistance, making adjustments to the prosthetic device in anticipation of changes in the user's environment or activity. User-Device Synchronization: AI can facilitate synchronization between the user's natural movements and the prosthetic device, creating a more seamless and integrated user experience.

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4 AI-driven optimization and learning

A fourth challenge in biomechatronics and prosthetics is to optimize and learn from the performance and behavior of the devices and the users. AI-driven optimization and learning can help achieve this by using reinforcement learning, neural networks, and data analytics to improve and adapt the functionality and efficiency of the devices. For example, some prosthetic knees can use AI to learn from the user's walking style and preferences, and optimize the parameters and settings of the device. Some prosthetic brains can use AI to learn from the user's cognitive and emotional states, and adjust the stimulation and modulation of the neural activity. AI-driven optimization and learning can also help the user to learn from their own and others' experiences, and enhance their skills and confidence.

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Dharunkumar Senthilkumar

| Machine Learning, Robotics and Control | MSc MPSYS at Chalmers University |
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Additionally, integrating AI into biomechatronics and prosthetics can facilitate real-time adjustments based on environmental factors, enabling devices to seamlessly adapt to various conditions and activities. This dynamic responsiveness enhances user experience and overall functionality. Furthermore, AI-driven personalized feedback mechanisms can empower users with insights into their biomechanical performance, fostering continuous improvement and a deeper understanding of their prosthetic devices.

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5 AI-supported integration and rehabilitation

A fifth challenge in biomechatronics and prosthetics is to integrate and rehabilitate the devices and the users into their social and physical environments. AI-supported integration and rehabilitation can help facilitate this by using virtual reality, augmented reality, and gamification to provide immersive and engaging experiences. For example, some prosthetic limbs can use AI to create realistic and interactive virtual environments, where the user can practice and train their motor skills and coordination. Some prosthetic organs can use AI to create augmented reality overlays, where the user can access and visualize relevant information and feedback. AI-supported integration and rehabilitation can also help the user to cope with their psychological and emotional challenges, and improve their well-being and quality of life.

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Dharunkumar Senthilkumar

| Machine Learning, Robotics and Control | MSc MPSYS at Chalmers University |
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Moreover, AI-driven integration in biomechatronics and prosthetics can extend beyond individual rehabilitation by fostering community engagement. Collaborative platforms leveraging AI can connect users, creating a supportive network for sharing experiences and insights. Additionally, AI-guided social integration features can assist users in navigating public spaces, enhancing their sense of inclusivity and independence. This comprehensive approach not only addresses physical rehabilitation but also contributes to the overall societal integration of individuals with biomechatronic devices.

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6 Here’s what else to consider

This is a space to share examples, stories, or insights that don’t fit into any of the previous sections. What else would you like to add?

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Dr. Daher Sayfeddine

Ph.D. (Robotics), D.Cert. CMI LEVEL 8, MEng.(Mechatronics & Int. Engineering), CMgr. FCMI, CEng MIET, PMP?, PRINCE2?, PMI-ACP?, PM LEVEL 6, PSM I?
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advanced prosthetic control system, brain-machine interface (BMI), predictive maintenance, NLP for control, cybersecurity.. all those are topics to be discussed in depth

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What are the latest trends and innovations in AI for biomechatronics and prosthetics?

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1 AI-powered sensors

2 AI-enabled communication

3 AI-based design and customization

4 AI-driven optimization and learning

5 AI-supported integration and rehabilitation

6 Here’s what else to consider

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