Italy
2021 - Present
Mental Economy Training (MET)
A combination of cutting edge software, designed to help maximise endurance and optimal mental performance for all those who employ high neural energies in highly stressful and competitive contexts
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Branding
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UI/UX
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Interaction
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Branding
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UI/UX
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Interaction
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Branding
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UI/UX
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Interaction
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Branding
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UI/UX
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Interaction
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Branding
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Case Study
Cognitive Optimization for Elite Performance
Project Scope
Mental Economy Training (MET)
The system combines biometric data, adaptive cognitive training, and real-time neural feedback in a cohesive digital experience deployed across wearables, large touch LCD screens, AR displays, tablets, and mobile devices.
The following details the research and design process behind MET, as documented through field photos, interface development, and hardware integration.
Phase 1: Contextual Research & Environments
Here is the real-world environment to understand user needs on site.
Photos Referenced:
Tactical gear setup in a dimly lit training facility
Headset Bio-sensor and eye-tracking headgear being tested
Athlete connected to EEG and heart rate variability monitors during test training
Key Observations:
Environments are physically and cognitively demanding — interfaces must be glanceable and low-distraction.
Biometric data is abundant but fragmented — users had multiple devices feeding inconsistent streams.
Offline operation is non-negotiable, especially in military or spacecraft scenarios.
Phase 2: Device Ecosystem Mapping
Based on our field research, it was important to catalog and prototype integration across the hardware ecosystem, consisting of:
Photos Reference
Wrist-worn HRV tracker with satellite uplink prototype
Data cable harness connected to a neural stimulation patch
Operator wearing a dry-electrode EEG headset
I designed modular device hub UI, allowing users to:
View real-time connectivity strength
Calibrate devices with one tap
Receive haptic feedback for signal dropouts
Log data offline with timestamped sync
This informed the "Device Sync Center" in the final IA.
Phase 3: Interface Design & Prototyping
Dashboard segmentation by training mode, mission mode, and review mode
Use of ring-based performance indicators, color-coded player stress thresholds
Visual System:
I aimed for a clean, HUD-inspired design language system used in cockpits and AR glasses. The interface used high-contrast monochrome palettes with occasional accent colors to signify state changes through a dark UI with cyan highlights.
Cognitive Load Rings: Expand/shrink based on mental effort and accuracy
Pulse Line Charts: Map heart rate, EEG spikes, and stress index over time
Glanceable Alerts: Use color-coded badges (green, yellow, red) for performance zones
All interfaces prioritized low-latency, high-contrast, and AR compatibility.
Phase 4:
Information Architecture Justification
A three-tiered IA structure:
Live Operations
"Home Library," "Device Connection," and "My Experience"(Training Feedback)
Training Mode & Insights
"Training"(official test), "Free practice"(allows peer-to-peer matches), comparative peer analytics
Device & Profile Management
User roles, biometric pairing, offline sync status
This structure allowed seamless navigation during both training and real-world deployment—confirmed through task-based usability tests
Outcome & Impact
Performance Improvement: Users reported a 25–40% improvement in focus and cognitive recovery rates within 4 weeks.
Adoption: Jannik Sinner breaking through the ATP Finals, assisted since 2021 at the Patti Tennis Center with a dedicated MET gym, and Axiom Space third commercial human spaceflight in the Jan 2024 mission to the International Space Station.
Interface Validation: Rated 9.1/10 for usability by spacecraft personnel in simulated space environment
Photos Referenced: Colonel Walter Villadei Mental Training
Conclusion
The MET platform emerged from the ground up — informed by environments, equipment, and people seen in these photos. This wasn’t a product imagined in isolation, but one prototyped in real physical environments, gym floors, and cockpit simulators.
My biggest lesson? In high-stakes performance, design clarity begins with mental clarity.
Case Study
Cognitive Optimization for Elite Performance
Project Scope
Mental Economy Training (MET)
The system combines biometric data, adaptive cognitive training, and real-time neural feedback in a cohesive digital experience deployed across wearables, large touch LCD screens, AR displays, tablets, and mobile devices.
The following details the research and design process behind MET, as documented through field photos, interface development, and hardware integration.
Phase 1: Contextual Research & Environments
Here is the real-world environment to understand user needs on site.
Photos Referenced:
Tactical gear setup in a dimly lit training facility
Headset Bio-sensor and eye-tracking headgear being tested
Athlete connected to EEG and heart rate variability monitors during test training
Key Observations:
Environments are physically and cognitively demanding — interfaces must be glanceable and low-distraction.
Biometric data is abundant but fragmented — users had multiple devices feeding inconsistent streams.
Offline operation is non-negotiable, especially in military or spacecraft scenarios.
Phase 2: Device Ecosystem Mapping
Based on our field research, it was important to catalog and prototype integration across the hardware ecosystem, consisting of:
Photos Reference
Wrist-worn HRV tracker with satellite uplink prototype
Data cable harness connected to a neural stimulation patch
Operator wearing a dry-electrode EEG headset
I designed modular device hub UI, allowing users to:
View real-time connectivity strength
Calibrate devices with one tap
Receive haptic feedback for signal dropouts
Log data offline with timestamped sync
This informed the "Device Sync Center" in the final IA.
Phase 3: Interface Design & Prototyping
Dashboard segmentation by training mode, mission mode, and review mode
Use of ring-based performance indicators, color-coded player stress thresholds
Visual System:
I aimed for a clean, HUD-inspired design language system used in cockpits and AR glasses. The interface used high-contrast monochrome palettes with occasional accent colors to signify state changes through a dark UI with cyan highlights.
Cognitive Load Rings: Expand/shrink based on mental effort and accuracy
Pulse Line Charts: Map heart rate, EEG spikes, and stress index over time
Glanceable Alerts: Use color-coded badges (green, yellow, red) for performance zones
All interfaces prioritized low-latency, high-contrast, and AR compatibility.
Phase 4:
Information Architecture Justification
A three-tiered IA structure:
Live Operations
"Home Library," "Device Connection," and "My Experience"(Training Feedback)
Training Mode & Insights
"Training"(official test), "Free practice"(allows peer-to-peer matches), comparative peer analytics
Device & Profile Management
User roles, biometric pairing, offline sync status
This structure allowed seamless navigation during both training and real-world deployment—confirmed through task-based usability tests
Outcome & Impact
Performance Improvement: Users reported a 25–40% improvement in focus and cognitive recovery rates within 4 weeks.
Adoption: Jannik Sinner breaking through the ATP Finals, assisted since 2021 at the Patti Tennis Center with a dedicated MET gym, and Axiom Space third commercial human spaceflight in the Jan 2024 mission to the International Space Station.
Interface Validation: Rated 9.1/10 for usability by spacecraft personnel in simulated space environment
Photos Referenced: Colonel Walter Villadei Mental Training
Conclusion
The MET platform emerged from the ground up — informed by environments, equipment, and people seen in these photos. This wasn’t a product imagined in isolation, but one prototyped in real physical environments, gym floors, and cockpit simulators.
My biggest lesson? In high-stakes performance, design clarity begins with mental clarity.
Case Study
Cognitive Optimization for Elite Performance
Project Scope
Mental Economy Training (MET)
The system combines biometric data, adaptive cognitive training, and real-time neural feedback in a cohesive digital experience deployed across wearables, large touch LCD screens, AR displays, tablets, and mobile devices.
The following details the research and design process behind MET, as documented through field photos, interface development, and hardware integration.
Phase 1: Contextual Research & Environments
Here is the real-world environment to understand user needs on site.
Photos Referenced:
Tactical gear setup in a dimly lit training facility
Headset Bio-sensor and eye-tracking headgear being tested
Athlete connected to EEG and heart rate variability monitors during test training
Key Observations:
Environments are physically and cognitively demanding — interfaces must be glanceable and low-distraction.
Biometric data is abundant but fragmented — users had multiple devices feeding inconsistent streams.
Offline operation is non-negotiable, especially in military or spacecraft scenarios.
Phase 2: Device Ecosystem Mapping
Based on our field research, it was important to catalog and prototype integration across the hardware ecosystem, consisting of:
Photos Reference
Wrist-worn HRV tracker with satellite uplink prototype
Data cable harness connected to a neural stimulation patch
Operator wearing a dry-electrode EEG headset
I designed modular device hub UI, allowing users to:
View real-time connectivity strength
Calibrate devices with one tap
Receive haptic feedback for signal dropouts
Log data offline with timestamped sync
This informed the "Device Sync Center" in the final IA.
Phase 3: Interface Design & Prototyping
Dashboard segmentation by training mode, mission mode, and review mode
Use of ring-based performance indicators, color-coded player stress thresholds
Visual System:
I aimed for a clean, HUD-inspired design language system used in cockpits and AR glasses. The interface used high-contrast monochrome palettes with occasional accent colors to signify state changes through a dark UI with cyan highlights.
Cognitive Load Rings: Expand/shrink based on mental effort and accuracy
Pulse Line Charts: Map heart rate, EEG spikes, and stress index over time
Glanceable Alerts: Use color-coded badges (green, yellow, red) for performance zones
All interfaces prioritized low-latency, high-contrast, and AR compatibility.
Phase 4:
Information Architecture Justification
A three-tiered IA structure:
Live Operations
"Home Library," "Device Connection," and "My Experience"(Training Feedback)
Training Mode & Insights
"Training"(official test), "Free practice"(allows peer-to-peer matches), comparative peer analytics
Device & Profile Management
User roles, biometric pairing, offline sync status
This structure allowed seamless navigation during both training and real-world deployment—confirmed through task-based usability tests
Outcome & Impact
Performance Improvement: Users reported a 25–40% improvement in focus and cognitive recovery rates within 4 weeks.
Adoption: Jannik Sinner breaking through the ATP Finals, assisted since 2021 at the Patti Tennis Center with a dedicated MET gym, and Axiom Space third commercial human spaceflight in the Jan 2024 mission to the International Space Station.
Interface Validation: Rated 9.1/10 for usability by spacecraft personnel in simulated space environment
Photos Referenced: Colonel Walter Villadei Mental Training
Conclusion
The MET platform emerged from the ground up — informed by environments, equipment, and people seen in these photos. This wasn’t a product imagined in isolation, but one prototyped in real physical environments, gym floors, and cockpit simulators.
My biggest lesson? In high-stakes performance, design clarity begins with mental clarity.
Description
The Formula Medicine team partnered with PwC Italia to created a mental training program for formula 1 racers and expanding to elite level athletes, military forces and even astronauts: Mental Economy Training (MET) and its Home Kit version. I'll discuss how developed a training software that retains users’ attention and help them develop their skills, what functions help with remote training, and what problems we ran into while adapting MET to different devices.
Description
The Formula Medicine team partnered with PwC Italia to created a mental training program for formula 1 racers and expanding to elite level athletes, military forces and even astronauts: Mental Economy Training (MET) and its Home Kit version. I'll discuss how developed a training software that retains users’ attention and help them develop their skills, what functions help with remote training, and what problems we ran into while adapting MET to different devices.
Description
The Formula Medicine team partnered with PwC Italia to created a mental training program for formula 1 racers and expanding to elite level athletes, military forces and even astronauts: Mental Economy Training (MET) and its Home Kit version. I'll discuss how developed a training software that retains users’ attention and help them develop their skills, what functions help with remote training, and what problems we ran into while adapting MET to different devices.
Team
PwC: 2 Project Manager
Formula Medicine: 2 medical teams, 2 coaching teams
Developers: 2
Designers: 1
Team
PwC: 2 Project Manager
Formula Medicine: 2 medical teams, 2 coaching teams
Developers: 2
Designers: 1
Team
PwC: 2 Project Manager
Formula Medicine: 2 medical teams, 2 coaching teams
Developers: 2
Designers: 1
MET x Axiom 3 Mission
About
During the Ax-3 mission, the crew members will represent their nations in low-Earth orbit (LEO) and perform scientific experiments and demonstrations that are of high national importance. Axiom Space’s crew of four astronauts will conduct more than 30 different experiments while aboard the space station.
Data collected through MET on ground, before and after the mission, as well as in flight will impact understanding of human physiology on Earth and on orbit, as well as advance scientific understanding, harness opportunities for industrial advancements, and develop technologies for humanity’s progress.
Axiom-3 Mission Space
https://www.axiomspace.com/missions/ax3
MET x Axiom 3 Mission
About
During the Ax-3 mission, the crew members will represent their nations in low-Earth orbit (LEO) and perform scientific experiments and demonstrations that are of high national importance. Axiom Space’s crew of four astronauts will conduct more than 30 different experiments while aboard the space station.
Data collected through MET on ground, before and after the mission, as well as in flight will impact understanding of human physiology on Earth and on orbit, as well as advance scientific understanding, harness opportunities for industrial advancements, and develop technologies for humanity’s progress.
Axiom-3 Mission Space
https://www.axiomspace.com/missions/ax3
MET x Axiom 3 Mission
About
During the Ax-3 mission, the crew members will represent their nations in low-Earth orbit (LEO) and perform scientific experiments and demonstrations that are of high national importance. Axiom Space’s crew of four astronauts will conduct more than 30 different experiments while aboard the space station.
Data collected through MET on ground, before and after the mission, as well as in flight will impact understanding of human physiology on Earth and on orbit, as well as advance scientific understanding, harness opportunities for industrial advancements, and develop technologies for humanity’s progress.
Axiom-3 Mission Space
https://www.axiomspace.com/missions/ax3
Project
Project
Project
Mental Economy Training (MET)
Training for the next big race or match at the Olympics goes beyond training one's body.
MET is configured as a methodological path of psychological transformation, where the athlete becomes the architect of his own mental evolution that allows to preserve brain energy, rationalizing cognitive resources and governing emotional dynamics in high-tension contexts.
Mechanics and Visual Style
At first, the MET interface was designed in a “Grunge” style, with aggressive lines, dark and fiery colors. We realized it influenced the perception of performers leading to more impulsive actions and prioritizing competition over a state of mental clarity and focus visible also through their body responses (increased heart rate, fidgeting, and anxiety levels).
Our target audience required a different approach.
Read Case study
Cognitive Optimization for Elite Performance
Project Scope
Mental Economy Training (MET)
The system combines biometric data, adaptive cognitive training, and real-time neural feedback in a cohesive digital experience deployed across wearables, large touch LCD screens, AR displays, tablets, and mobile devices.
The following details the research and design process behind MET, as documented through field photos, interface development, and hardware integration.
Phase 1: Contextual Research & Environments
Here is the real-world environment to understand user needs on site.
Photos Referenced:
Tactical gear setup in a dimly lit training facility
Headset Bio-sensor and eye-tracking headgear being tested
Athlete connected to EEG and heart rate variability monitors during test training
Key Observations:
Environments are physically and cognitively demanding — interfaces must be glanceable and low-distraction.
Biometric data is abundant but fragmented — users had multiple devices feeding inconsistent streams.
Offline operation is non-negotiable, especially in military or spacecraft scenarios.
Phase 2: Device Ecosystem Mapping
Based on our field research, it was important to catalog and prototype integration across the hardware ecosystem, consisting of:
Photos Reference
Wrist-worn HRV tracker with satellite uplink prototype
Data cable harness connected to a neural stimulation patch
Operator wearing a dry-electrode EEG headset
I designed modular device hub UI, allowing users to:
View real-time connectivity strength
Calibrate devices with one tap
Receive haptic feedback for signal dropouts
Log data offline with timestamped sync
This informed the "Device Sync Center" in the final IA.
Phase 3: Interface Design & Prototyping
Dashboard segmentation by training mode, mission mode, and review mode
Use of ring-based performance indicators, color-coded player stress thresholds
Visual System:
I aimed for a clean, HUD-inspired design language system used in cockpits and AR glasses. The interface used high-contrast monochrome palettes with occasional accent colors to signify state changes through a dark UI with cyan highlights.
Cognitive Load Rings: Expand/shrink based on mental effort and accuracy
Pulse Line Charts: Map heart rate, EEG spikes, and stress index over time
Glanceable Alerts: Use color-coded badges (green, yellow, red) for performance zones
All interfaces prioritized low-latency, high-contrast, and AR compatibility.
Phase 4:
Information Architecture Justification
A three-tiered IA structure:
Live Operations
"Home Library," "Device Connection," and "My Experience"(Training Feedback)
Training Mode & Insights
"Training"(official test), "Free practice"(allows peer-to-peer matches), comparative peer analytics
Device & Profile Management
User roles, biometric pairing, offline sync status
This structure allowed seamless navigation during both training and real-world deployment—confirmed through task-based usability tests
Outcome & Impact
Performance Improvement: Users reported a 25–40% improvement in focus and cognitive recovery rates within 4 weeks.
Adoption: Jannik Sinner breaking through the ATP Finals, assisted since 2021 at the Patti Tennis Center with a dedicated MET gym, and Axiom Space third commercial human spaceflight in the Jan 2024 mission to the International Space Station.
Interface Validation: Rated 9.1/10 for usability by spacecraft personnel in simulated space environment
Photos Referenced: Colonel Walter Villadei Mental Training
Conclusion
The MET platform emerged from the ground up — informed by environments, equipment, and people seen in these photos. This wasn’t a product imagined in isolation, but one prototyped in real physical environments, gym floors, and cockpit simulators.
My biggest lesson? In high-stakes performance, design clarity begins with mental clarity.
Read Case study
Cognitive Optimization for Elite Performance
Project Scope
Mental Economy Training (MET)
The system combines biometric data, adaptive cognitive training, and real-time neural feedback in a cohesive digital experience deployed across wearables, large touch LCD screens, AR displays, tablets, and mobile devices.
The following details the research and design process behind MET, as documented through field photos, interface development, and hardware integration.
Phase 1: Contextual Research & Environments
Here is the real-world environment to understand user needs on site.
Photos Referenced:
Tactical gear setup in a dimly lit training facility
Headset Bio-sensor and eye-tracking headgear being tested
Athlete connected to EEG and heart rate variability monitors during test training
Key Observations:
Environments are physically and cognitively demanding — interfaces must be glanceable and low-distraction.
Biometric data is abundant but fragmented — users had multiple devices feeding inconsistent streams.
Offline operation is non-negotiable, especially in military or spacecraft scenarios.
Phase 2: Device Ecosystem Mapping
Based on our field research, it was important to catalog and prototype integration across the hardware ecosystem, consisting of:
Photos Reference
Wrist-worn HRV tracker with satellite uplink prototype
Data cable harness connected to a neural stimulation patch
Operator wearing a dry-electrode EEG headset
I designed modular device hub UI, allowing users to:
View real-time connectivity strength
Calibrate devices with one tap
Receive haptic feedback for signal dropouts
Log data offline with timestamped sync
This informed the "Device Sync Center" in the final IA.
Phase 3: Interface Design & Prototyping
Dashboard segmentation by training mode, mission mode, and review mode
Use of ring-based performance indicators, color-coded player stress thresholds
Visual System:
I aimed for a clean, HUD-inspired design language system used in cockpits and AR glasses. The interface used high-contrast monochrome palettes with occasional accent colors to signify state changes through a dark UI with cyan highlights.
Cognitive Load Rings: Expand/shrink based on mental effort and accuracy
Pulse Line Charts: Map heart rate, EEG spikes, and stress index over time
Glanceable Alerts: Use color-coded badges (green, yellow, red) for performance zones
All interfaces prioritized low-latency, high-contrast, and AR compatibility.
Phase 4:
Information Architecture Justification
A three-tiered IA structure:
Live Operations
"Home Library," "Device Connection," and "My Experience"(Training Feedback)
Training Mode & Insights
"Training"(official test), "Free practice"(allows peer-to-peer matches), comparative peer analytics
Device & Profile Management
User roles, biometric pairing, offline sync status
This structure allowed seamless navigation during both training and real-world deployment—confirmed through task-based usability tests
Outcome & Impact
Performance Improvement: Users reported a 25–40% improvement in focus and cognitive recovery rates within 4 weeks.
Adoption: Jannik Sinner breaking through the ATP Finals, assisted since 2021 at the Patti Tennis Center with a dedicated MET gym, and Axiom Space third commercial human spaceflight in the Jan 2024 mission to the International Space Station.
Interface Validation: Rated 9.1/10 for usability by spacecraft personnel in simulated space environment
Photos Referenced: Colonel Walter Villadei Mental Training
Conclusion
The MET platform emerged from the ground up — informed by environments, equipment, and people seen in these photos. This wasn’t a product imagined in isolation, but one prototyped in real physical environments, gym floors, and cockpit simulators.
My biggest lesson? In high-stakes performance, design clarity begins with mental clarity.
Read Case study
Cognitive Optimization for Elite Performance
Project Scope
Mental Economy Training (MET)
The system combines biometric data, adaptive cognitive training, and real-time neural feedback in a cohesive digital experience deployed across wearables, large touch LCD screens, AR displays, tablets, and mobile devices.
The following details the research and design process behind MET, as documented through field photos, interface development, and hardware integration.
Phase 1: Contextual Research & Environments
Here is the real-world environment to understand user needs on site.
Photos Referenced:
Tactical gear setup in a dimly lit training facility
Headset Bio-sensor and eye-tracking headgear being tested
Athlete connected to EEG and heart rate variability monitors during test training
Key Observations:
Environments are physically and cognitively demanding — interfaces must be glanceable and low-distraction.
Biometric data is abundant but fragmented — users had multiple devices feeding inconsistent streams.
Offline operation is non-negotiable, especially in military or spacecraft scenarios.
Phase 2: Device Ecosystem Mapping
Based on our field research, it was important to catalog and prototype integration across the hardware ecosystem, consisting of:
Photos Reference
Wrist-worn HRV tracker with satellite uplink prototype
Data cable harness connected to a neural stimulation patch
Operator wearing a dry-electrode EEG headset
I designed modular device hub UI, allowing users to:
View real-time connectivity strength
Calibrate devices with one tap
Receive haptic feedback for signal dropouts
Log data offline with timestamped sync
This informed the "Device Sync Center" in the final IA.
Phase 3: Interface Design & Prototyping
Dashboard segmentation by training mode, mission mode, and review mode
Use of ring-based performance indicators, color-coded player stress thresholds
Visual System:
I aimed for a clean, HUD-inspired design language system used in cockpits and AR glasses. The interface used high-contrast monochrome palettes with occasional accent colors to signify state changes through a dark UI with cyan highlights.
Cognitive Load Rings: Expand/shrink based on mental effort and accuracy
Pulse Line Charts: Map heart rate, EEG spikes, and stress index over time
Glanceable Alerts: Use color-coded badges (green, yellow, red) for performance zones
All interfaces prioritized low-latency, high-contrast, and AR compatibility.
Phase 4:
Information Architecture Justification
A three-tiered IA structure:
Live Operations
"Home Library," "Device Connection," and "My Experience"(Training Feedback)
Training Mode & Insights
"Training"(official test), "Free practice"(allows peer-to-peer matches), comparative peer analytics
Device & Profile Management
User roles, biometric pairing, offline sync status
This structure allowed seamless navigation during both training and real-world deployment—confirmed through task-based usability tests
Outcome & Impact
Performance Improvement: Users reported a 25–40% improvement in focus and cognitive recovery rates within 4 weeks.
Adoption: Jannik Sinner breaking through the ATP Finals, assisted since 2021 at the Patti Tennis Center with a dedicated MET gym, and Axiom Space third commercial human spaceflight in the Jan 2024 mission to the International Space Station.
Interface Validation: Rated 9.1/10 for usability by spacecraft personnel in simulated space environment
Photos Referenced: Colonel Walter Villadei Mental Training
Conclusion
The MET platform emerged from the ground up — informed by environments, equipment, and people seen in these photos. This wasn’t a product imagined in isolation, but one prototyped in real physical environments, gym floors, and cockpit simulators.
My biggest lesson? In high-stakes performance, design clarity begins with mental clarity.
MET into Space with Axiom-3
The first all-European commercial astronaut mission to the International Space Station, Axiom Mission 3 (Ax-3) redefines the pathway to low-Earth orbit for nations around the globe.
The goal of this project is to investigate whether specific skills and cognitive abilities (concentration, focused attention, reactivity, stress management, memory, and others) are affected by spaceflight and how MET™ could be implemented for future crew.
Data collected by Axiom Space’s crew of four astronauts on more than 30 different experiments on ground, before and after the mission as well as in flight will impact understanding of human physiology on Earth and on orbit, as well as advance scientific understanding, harness opportunities for industrial advancements, and develop technologies for humanity’s progress.
Learn more on https://www.axiomspace.com/research/mental-economy
