Science
Why movement patterns and analysis are central in medicine and care
- They provide valuable insights to enhance physical performance,
- promote targeted rehabilitation,
- maintain mobility in old age and counteract functional decline.
Our scientific partners






Previously expensive cutting-edge medicine
Traditionally, movement analysis is performed in high-tech laboratories.
They require specialized equipment and highly qualified personnel. This often leads to high costs and limits the availability of such examinations to specialized clinics.

Falls in old age: A pain point for everyone
No pill, no vaccine works: Limited mobility is a significant risk factor. Falls pose a considerable health threat, particularly for people over 60.
Falls are among the most common causes of injuries and disabilities in old age. They have serious consequences for both those affected and society: costs in the billions, increased care needs.
Therefore, fall risk assessment and prevention are at the center of our work.

We make cutting-edge medicine affordable
Our mission is to make scientifically based movement analysis and fall risk assessments accessible to everyone.
We bridge the gap between complex research and practical everyday application to make the benefits of these analyses available to everyone.
Our standard: Peer-reviewed
For the continuous development of our products, we work closely with scientific partners and conduct ongoing studies.
We publish the results in renowned, peer-reviewed journals to ensure the highest standards of evidence-based research.

Digital fall risk analysis
A comprehensive fall risk analysis is crucial to understand the factors that lead to falls and prevent them in a targeted way.
Our fall risk assessments are based on national and international guidelines, ensuring our approach always meets current scientific and clinical standards.

AI gait analysis + Digital questionnaires
We combine video-based gait analysis with digital questionnaires.
This allows us to objectively assess individual gait characteristics and capture risk factors. These movement parameters are crucial for understanding fall-related mobility risk and planning appropriate measures to address it.
They have been validated against the gold standard (Azhand et al., 2020).

Fall risk: A multifactorial approach
Using a multifactorial assessment approach, we calculate a uniform and easily interpretable value – the fall risk as a percentage.
This score combines various fall risk factors into a single, understandable metric. It provides a comprehensive overview of a person's fall risk.
This enables healthcare professionals and caregivers at home to make informed decisions about fall prevention.

Score von 0 bis 100
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A score of 0 means no fall risk factors are present,
- while a score of 100 indicates the complete presence of all identified risk factors.


Six categories, up to 14 risk factors
The fall risk score integrates six categories of up to 14 risk factors, each representing specific aspects of fall risk.
This multifactorial approach ensures that fall risk is assessed from multiple perspectives. It provides a holistic understanding of the individual's condition, enables precise progress tracking, and allows for tailored prevention measures.
Weighting
Each risk factor within the score is weighted based on proven fall risk models with demonstrated diagnostic accuracy.
Critical risk factors that have the greatest impact on fall risk receive double weighting to highlight areas that require special attention.

How the fall risk score is validated?
Our fall risk score has been validated to test its specificity and sensitivity and ensure it represents a reliable tool for identifying people at risk of falls.

Focus on Seniors
Validation studies, conducted primarily with a population of seniors in residential care facilities, showed high diagnostic accuracy (Rabe et al., 2020).
A recently conducted internal study in outpatient settings confirmed similar results and supports the applicability of the score in different environments.
(Motamedi et al., 2024, currently in preparation for publication in a peer-reviewed journal)

Correlation with TuG & Co.
Additionally, our fall risk score shows significant correlation with traditional fall risk assessments (e.g., Timed Up and Go), ensuring alignment with established methods and supporting its reliability.
(Strutz et al., 2022)

The traffic light system: Clear thresholds for practical application
To improve the practical applicability of the fall risk score, we have defined clinically relevant thresholds that categorize risk levels. They provide healthcare professionals, caregivers, and older adults with concrete action recommendations. Additionally,
Minimal Clinically Important Differences (MCIDs) have been established that indicate the smallest measurable change in the fall risk score. The MCIDs reflect what has improved or worsened in fall risk.
(Alves et al., 2024)

Evidence-based fall prevention recommendations
In addition to fall risk assessment, our fall prevention approach includes specific, evidence-based recommendations.
These tailored measures specifically address the risk factors identified in the individual fall risk assessment.
The recommendations are designed to reduce risk factors, lower fall risk, and improve mobility - in accordance with clinical care guidelines.

Effectiveness continuously monitored
In residential facilities, our fall prevention recommendations have been validated through multiple studies, including work by Dahms et al. (2023) and Alves et al. (2024).
These were presented at the Digital Health & Telemedicine Conference and the European Falls Fest. They confirm the effectiveness of our approach.
For outpatient settings, we conducted an intra-individual study evaluating the effectiveness of our recommendations under more dynamic, real-world conditions.
Our foundation
ISO 13485 & 27001
Patented AI
Reducing falls in old age was the starting point of LINDERA. This led us to create a simple app - and we make this simplicity possible with our computer vision AI.
Our scientific partners
- Prof. Dr. Jürgen Zerth and Sebastian Müller (Katholische Universität Eichstätt-Ingolstadt)
- Dr. André Baumgart (Universität Heidelberg)
- Prof. Dr. med. Wolfgang Pommer ( Charité – Universitätsmedizin Berlin)
- Dr. Sandra Strube-Lahmann, Prof. Dr. Nils Lahmann, Susann Vorweg-Gall (Charité – Universitätsmedizin Berlin)
- Dr. Nadine Lang-Richter (Fraunhofer-Institut für Integrierte Schaltungen IIS)
Would you like to work with us?
Join our team, participate in research projects, co-author publications with us, or integrate our technology into your research projects - we are open to collaboration.