Research
Beautiful teamwork – connect with team members
Measuring communication in teams for happier, higher performing teams. The quality of teamwork is also dependent on background music, immersion into nature, and well-designed architectural spaces.
In our research we study communication in teams through face-to-face and online social media interaction measured with the Happimetrics toolkit. The goal is to improve PERMA of participants in the team.
Subproject: identifying ideal team members based on personal values. We build AI models predicting personal values based on the words people use, and identify optimal combinations of personal values depending on the task of the team.
Subproject: Detecting lies The goal of this project is to build a machine learning model that will detect lies based on body posture and facial expression.
In our research we study communication in teams through face-to-face and online social media interaction measured with the Happimetrics toolkit. The goal is to improve PERMA of participants in the team.
Subproject: identifying ideal team members based on personal values. We build AI models predicting personal values based on the words people use, and identify optimal combinations of personal values depending on the task of the team.
Subproject: Detecting lies The goal of this project is to build a machine learning model that will detect lies based on body posture and facial expression.
Beautiful music – connect musicians and audience
Measuring the impact of music on musicians and audience, with the goal of improving musical performances leading to a better experience for the audience, learning and teaching how to play musical instruments and perform in live concerts.
The goal of this research project is to develop a multimodal emotion sensing toolkit for musicians that can be used to improve music education and musical performances. Our approach combines emotion sensing by face emotion recognition (FER), body signal analysis using the Happimeter, a smartwatch-based solution, and plant-based emotion sensing.
Applying our approach to music education, we have already run a series of pilots with jazz musicians at concerts and rehearsals, for instance at the Berklee College of Music. Our most recent project is with Jazzaar, led by Fritz Renold, a 31-year music project located in Aarau, Switzerland.
The goal of this research project is to develop a multimodal emotion sensing toolkit for musicians that can be used to improve music education and musical performances. Our approach combines emotion sensing by face emotion recognition (FER), body signal analysis using the Happimeter, a smartwatch-based solution, and plant-based emotion sensing.
Applying our approach to music education, we have already run a series of pilots with jazz musicians at concerts and rehearsals, for instance at the Berklee College of Music. Our most recent project is with Jazzaar, led by Fritz Renold, a 31-year music project located in Aarau, Switzerland.
Beautiful nature – connect the human to nature
Measuring the impact of humans on plants and measuring the impact of plants on humans. Towards that goal, a device that measures changes in the action potential of plants in response to human emotions shown near the plant, will be built, consisting of dedicated hardware and software.
The Eurythmy subproject measures the influence of human interaction on plants. Salad, beans, and tomatoes are treated with eurythmy. The change in action potential is measured for untreated, single treated, and multiple treated plants using the plant spikerbox. Additionally, the change in action potential is also measured between different persons doing eurythmy.
In a second project a machine learning model for emotion tracking with the plant spikerbox and basil is developed. This is combined with team experiments. The action potential change for different emotions for a large cohort of study subjects is measured and taken as input data to build the model. In a later phase the goal is to build dedicated hardware for emotion tracking with a plant. This will be a non-intrusive, privacy respecting emotion tracking device which can be flexibly used for many different settings.
Subproject measuring emotions of animals: using AI models, we will identify wellbeing stress, and illnesses of dogs, cats, horses, and cows from their body posture, facial expressions, voice, and body temperature.
The Eurythmy subproject measures the influence of human interaction on plants. Salad, beans, and tomatoes are treated with eurythmy. The change in action potential is measured for untreated, single treated, and multiple treated plants using the plant spikerbox. Additionally, the change in action potential is also measured between different persons doing eurythmy.
In a second project a machine learning model for emotion tracking with the plant spikerbox and basil is developed. This is combined with team experiments. The action potential change for different emotions for a large cohort of study subjects is measured and taken as input data to build the model. In a later phase the goal is to build dedicated hardware for emotion tracking with a plant. This will be a non-intrusive, privacy respecting emotion tracking device which can be flexibly used for many different settings.
Subproject measuring emotions of animals: using AI models, we will identify wellbeing stress, and illnesses of dogs, cats, horses, and cows from their body posture, facial expressions, voice, and body temperature.
Beautiful architecture – connect the human to the built environment
Measuring the impact of well-designed and poorly designed architectural spaces on human wellbeing, and teamwork performance.
The goal is to measure the influence of the built environment on happiness and teamwork. This will include measuring architectural influence both on the macro building level, and the micro room level. We will measure emotions through FER in interaction with different types of buildings, for instance in museums, churches, or supermarkets, applying the 14 design patterns of biophilic design.
On the team level we will measure communication intensity and emotions for comparable teams in different rooms, for instance small workgroup rooms, large, shared office space, or in the park. We hypothesize that the more a team room resembles a landscape in the park, the higher will the productivity of the team be.
The goal is to measure the influence of the built environment on happiness and teamwork. This will include measuring architectural influence both on the macro building level, and the micro room level. We will measure emotions through FER in interaction with different types of buildings, for instance in museums, churches, or supermarkets, applying the 14 design patterns of biophilic design.
On the team level we will measure communication intensity and emotions for comparable teams in different rooms, for instance small workgroup rooms, large, shared office space, or in the park. We hypothesize that the more a team room resembles a landscape in the park, the higher will the productivity of the team be.