IIoT-Projects GmbH / iMouse

Traditionally, in biomedical animal research, laboratory rodents are individually examined in test apparatuses outside their home cages at selected time points.

However, the outcome of such tests can be influenced by the novel environment, the time of day, separation from the social group, or the presence of an experimenter.

Moreover, valuable information may be missed when the animals are only monitored in short periods.

These issues can be overcome by longitudinal monitoring mice and rats in their home cages.

When the animals are tested outside their home cage, the time of day can play a critical role, too.

Although rats and mice are nocturnal/crepuscular animals, experiments are often carried out during the daytime when the lights are turned on in the animal and experimental rooms.

We as the iMouse team are developing the iMouse solution.

This approach allows researchers to collect data on animals’ without disturbing their natural behaviors.

The primary goals of digital home cage monitoring are:

• Non-Invasive Data Collection: Traditional methods of monitoring animals often involve disturbing their environment, leading to altered behavior and stress.
• Digital home cage monitoring aims to minimize this disruption by collecting data using non-invasive techniques.
• Long-Term Observation: With continuous monitoring, researchers can study animals over extended periods, providing insights into their daily routines, circadian rhythms, and responses to various stimuli.
• High-Quality Data: Digital monitoring can provide more accurate and detailed data than manual observations, reducing human error and bias.
• Reduced Stress: By allowing animals to remain in their familiar environment, digital home cage monitoring reduces stress compared to procedures involving frequent handling or relocation.
• Multiple Parameters: Researchers can monitor various parameters, such as movement, activity levels, feeding patterns, social interactions.
• Automation: Automation of data collection and analysis minimizes the need for constant human intervention and increases the efficiency of data processing.
  Generation of training data: Digital monitoring can be used as a source to generate excellent training data.