Introduction: Clinical posturology, a discipline dedicated to the study of human postural control, has significantly evolved through the integration of interdisciplinary approaches, including neuroscience, biomechanics, and artificial intelligence (AI). This evolution raises epistemological questions regarding objectivity, reproducibility of measurements, and the management of variability in nonlinear dynamic systems.

Objective: To examine the epistemological foundations of clinical posturology, with an emphasis on the use of AI to improve the assessment and management of postural control.

Methodology: A critical literature review was conducted, drawing on major contemporary epistemological frameworks (Popper, Kuhn, Lakatos, among others) and their application to clinical posturology. This was complemented with recent studies on the use of AI in interpreting stabilometric data.

Results: Objectivity in posturology was found not to lie in eliminating variability, but in its critical and contextual management. AI emerges as a key tool in identifying center of pressure (COP) oscillation patterns, enhancing reproducibility, and personalizing clinical interventions. The need for an interdisciplinary approach to address the complexity of postural control was emphasized.

Conclusion: The integration of AI into clinical posturology addresses essential epistemological challenges, such as variability and hypothesis falsifiability. This approach contributes to establishing posturology as an autonomous scientific discipline and promotes more precise and adaptive clinical practices.

Keywords: Applied epistemology, clinical posturology, postural control, artificial intelligence, nonlinear dynamic systems.

Postural control is an essential process for human stability and balance (Shumway-Cook & Woollacott, 2017). This process is regulated by the tonic postural system (Gagey, 1988), which is responsible for maintaining upright posture and body orientation in space. Clinical posturology, the discipline devoted to the study of this system (Bricot, 2014; Gagey & Weber, 2001), has undergone significant development in recent decades, adopting an interdisciplinary approach that incorporates contributions from neuroscience, biomechanics, cybernetics, computer science, and health sciences. This integration aims to understand the dynamics of postural control under both normal and pathological conditions.

Among the most prominent tools in this field is stabilometry, which allows for the measurement and analysis of body center of pressure (COP) oscillations using force platforms. This technique has become a fundamental resource for the objective assessment of postural stability (Kapteyn et al., 1983). However, alongside these methodological advances, epistemological questions have emerged that warrant attention. The inherent complexity of postural control, its adaptive nature, and the interaction of multiple sensory and motor subsystems pose challenges to the production, organization, and validation of scientific knowledge in clinical posturology.

Although stabilometry has facilitated the quantification of key variables—such as sway surface area, sway velocity, and the Romberg coefficient—its implementation has sparked debates concerning the objectivity, validity, and reproducibility of the obtained data (Asai, 2016; Błaszczyk & Beck, 2023; Gagey, 2020b). Therefore, it becomes essential to examine the epistemological issues associated with knowledge construction in this field.

To address these questions, this article draws on contributions from contemporary epistemology, reviewing the theories of Popper, Kuhn, Lakatos, Feyerabend, Hume, Kant, and Bernard. Perspectives from cybernetics and complex systems theory are also incorporated to offer a comprehensive analysis. These frameworks enable the exploration of issues such as hypothesis falsifiability (Popper), paradigm shifts (Kuhn), the logic of research programs (Lakatos), and the importance of interdisciplinarity (Feyerabend).

The main objective of this article is to examine the epistemological foundations underlying clinical posturology, with particular emphasis on the study of postural control through stabilometry.

The article is structured into three main sections. First, it presents the historical background of posturology, highlighting the shift from a predominantly biomechanical approach to a cybernetic-systemic perspective. Second, it explores the epistemological foundations of the discipline, focusing on the concepts of falsifiability, interdisciplinarity, and scientific objectivity. Finally, a critical discussion is offered regarding the epistemological implications of research in clinical posturology, with an emphasis on the challenges posed by the validity and reproducibility of stabilometric measurements.

This reflection seeks to contribute to the current debate on the construction of scientific knowledge in clinical posturology, promoting a critical analysis that can lead to more robust and rigorous research practices.

Historical Background of Clinical Posturology

Clinical posturology, as a discipline devoted to the study of human postural control, has undergone a conceptual and epistemological evolution that reflects the transition from a mechanistic approach to a cybernetic and systemic perspective (Bricot, 2014; Gagey & Weber, 2001; Shumway-Cook & Woollacott, 2017). This evolution has been made possible by the interdisciplinary integration of fields such as neurophysiology, biomechanics, cybernetics, and systems theory, giving rise to key tools such as stabilometry (Kapteyn et al., 1983; Scoppa et al., 2013), which is used to objectively assess postural stability by recording the center of pressure (COP).

The origins of posturology can be traced back to Ancient Greece, where Aristotle reflected on the capacity of living beings to remain upright, although lacking the concept of muscular tone. Later, Galen (131–201 CE) introduced the notion of antigravity tonic activity, highlighting the importance of sustained muscle contraction. In the modern era, René Descartes (1596–1650) conceptualized the human body as a machine, establishing a biomechanical paradigm that influenced positivist medicine. Giovanni Borelli (1608–1679), for his part, advanced the analysis of posture in relation to gravity, while Charles Bell (1774–1842) opened new perspectives by questioning the mechanisms of upright posture. The introduction of the Romberg test by Moritz H. Romberg (1840) represented a milestone in the clinical assessment of postural stability (Gagey, 2011).

The 19th and early 20th centuries were marked by the influence of positivism, promoting the search for universal laws through the elimination of variability. Claude Bernard’s experimental medicine emphasized the importance of controlled experimentation, laying the groundwork for the implementation of stabilometry, which applies standardized parameters in its assessments (Hsu et al., 2009; Ohlendorf et al., 2020; Patti et al., 2018; Schwesig et al., 2013). However, the discovery of intersubject and intrasubject variability in stabilometric recordings challenged this reductionist approach, favoring an epistemological reconfiguration that acknowledges the complexity of postural control.

The paradigm shift was consolidated with the incorporation of cybernetics and general systems theory. Norbert Wiener (1948) introduced the notion of feedback as a central principle of postural control, emphasizing the comparison between sensory inputs and internal references. Ludwig von Bertalanffy (1968) contributed the vision of organisms as open systems, stressing their constant interaction with the environment. These concepts enabled the understanding of posture not as a static position, but as a dynamic and adaptive equilibrium (Bois, 2010; Peterka, 2018). The "inverted pendulum" model proposed by Nashner (Nashner & McCollum, 1985) reinforced this view by conceptualizing the body as an unstable system that modulates its base of support to maintain stability.

The 1970s marked a turning point with the consolidation of clinical posturology as an autonomous discipline. Pierre-Marie Gagey and Bernard Weber adopted Popperian logic, proposing that posturological statements must be falsifiable to hold scientific validity (Gagey & Weber, 2001; Gagey & Weber, 2010). Within this framework, the concept of Postural Deficiency Syndrome (PDS) was introduced, described by Da Cunha (Martins Da Cunha, 1987), providing a clinical diagnosis for patients presenting symptoms such as dizziness, instability, and chronic pain, which had not previously been associated with the tonic postural system.

Today, clinical posturology is grounded in an interdisciplinary and systemic paradigm that integrates neuroscience, biomechanics, cybernetics, and computer science. Postural control is recognized as a nonlinear dynamic system with emergent and adaptive behavior (Conde-Vázquez et al., 2024). This contemporary approach aligns with evidence-based medicine (EBM), yet goes beyond it by emphasizing clinical personalization and interindividual variability (Saborido, 2020). The interpretation of stabilometric records is far from linear—it incorporates contextual factors and tailors interventions to the specific needs of each patient. The standardization of population references and protocols remains essential, but is now addressed from a perspective that accepts the inherent uncertainty of biological and clinical processes (Bizzo et al., 1985; Błaszczyk & Beck, 2023; Gagey, 2020b, 2020a; Scoppa et al., 2013; Winter et al., 1998).

Epistemological Foundations of Clinical Posturology

Clinical posturology faces several epistemological challenges related to the definition of its object of study, the validity and reproducibility of its measurement methods, and the need for an interdisciplinary theoretical foundation. As in many emerging sciences, posturology lacks a single, consolidated paradigm, which raises the issue of justifying the objectivity of its procedures and the coherence of its theoretical models. From the perspective of the philosophy of medicine, these challenges reflect the intrinsic difficulties of clinical practice, where objectivity is contextual and adaptive, and individual variability becomes a central factor in decision-making (Reiss & Ankeny, 2022).

Postural control, the object of study in posturology, falls within the domain of nonlinear dynamic systems. It involves sensory subsystems (visual, vestibular, and proprioceptive) that interact to regulate human balance (Bucci & Villeneuve, 2022; Foisy & Kapoula, 2016; Gagey & Weber, 2001; Ivanenko & Gurfinkel, 2018; Peterka, 2018; Shumway-Cook & Woollacott, 2017). The introduction of stabilometry enabled a shift from a primarily qualitative to a quantitative and objective assessment of posture, through the recording of the center of pressure (COP). However, the complexity of this phenomenon generates epistemological problems that can be grouped into four main categories: definition of the object of study, objectivity and reproducibility of measurements, interdisciplinarity and theoretical coherence, and hypothesis falsifiability.

One of the primary challenges lies in the conceptual definition of postural control. Historically, it has been interpreted from automatic reflex posture models (Sherrington and Magnus) to an emergent process within a nonlinear dynamic system (Nashner & McCollum, 1985; Wiener, 1948; Bertalanffy, 1968). From a Kantian perspective, postural control cannot be grasped as the “thing-in-itself” (Ding an sich), but rather as a phenomenon constructed from sensory experience, implying that posturology does not measure posture directly but interprets COP oscillations through theoretical categories (Gagey et al., 1998). This underscores the need for conceptual unification within the scientific community to enhance the discipline's operability and definitional consensus.

The objectivity and reproducibility of stabilometric measurements constitute another fundamental issue. The variability of COP recordings raises doubts about data consistency, even under similar conditions (De Blasiis et al., 2023). From David Hume’s perspective (1988), the problem of induction makes it difficult to ensure that past observations will persist in future cases. In clinical practice, this translates into the impossibility of ensuring consistent postural patterns across sessions. The philosophy of medicine acknowledges that such inter- and intra-individual variability is inherent to clinical practice and must be managed through concepts such as contextual objectivity. In this sense, the establishment of normative population references becomes a key tool for interpreting measurements within an applicable and meaningful framework (Gagey & Weber, 2010).

Mario Bunge (2012) argues that scientific objectivity does not lie in eliminating subjectivity but in developing operational procedures to control it. In posturology, the stabilometric platform exemplifies this by enabling comparable measurements through standardized parameters. However, operational reproducibility does not imply identical results but rather data that, under controlled conditions, are consistent and clinically relevant. In this context, artificial intelligence (AI) has emerged as a key tool to improve the precision and personalization of stabilometric interpretations, identifying subtle patterns in COP data and facilitating personalized medicine (Koltermann et al., 2024).

Interdisciplinarity presents a third challenge, as posturology integrates concepts from neuroscience, biomechanics, cybernetics, and computer science—disciplines that do not always share conceptual coherence. The philosophy of medicine supports this pluralism, recognizing, as Feyerabend suggested, that methodological diversity enriches scientific knowledge. However, this integration demands efforts to harmonize theories and ensure that the proposed models are clinically applicable and coherent.

Finally, the falsifiability of hypotheses—proposed by Karl Popper as the criterion of scientific demarcation—faces limitations in posturology due to the inherent variability of measurements. A negative result may stem from such variability rather than true refutation. Lakatos suggests addressing this issue through research programs that include auxiliary hypotheses, allowing for the validation of probabilistic models rather than the pursuit of absolute certainties. In clinical practice, this involves seeking statistical correlations—such as between age and COP oscillation—while recognizing the probabilistic and non-deterministic nature of findings.

Epistemological Implications of Research in Clinical Posturology

The epistemological challenges of clinical posturology affect not only theoretical knowledge production but also research practice, professional training, and academic dissemination. The difficulties associated with defining the object of study, achieving measurement objectivity, managing theoretical interdisciplinarity, and falsifying hypotheses cannot be definitively resolved but can be addressed through appropriate strategies. In this context, the integration of AI constitutes a key epistemological response, as it helps manage the uncertainty inherent in nonlinear dynamic systems by facilitating pattern identification, data classification, and behavior prediction.

From the philosophy of medicine standpoint, these challenges resemble those found in clinical practice, where intersubject variability and the need for individualized approaches demand a more contextual, less mechanistic model. In this regard, contextual objectivity becomes a crucial concept in posturology: the interpretation of stabilometric records should not rely on obtaining invariable values but on the capacity to critically contextualize the data from a clinical and adaptive perspective. AI exemplifies this principle by enabling the management of variability, as its algorithms classify COP records based on emergent patterns derived from the data themselves rather than preexisting theories.

In scientific research, AI is proving to be an essential tool for addressing issues of objectivity, reproducibility, and hypothesis testing. The reproducibility of stabilometric recordings has historically been compromised by inter- and intra-subject variability, influenced by factors such as attention, initial foot position, or participant fatigue (Kataoka et al., 2018). From Hume's (1988) view, the impossibility of rationally justifying the belief in nature’s uniformity undermines any claim to scientific objectivity as absolute certainty. In medical philosophy, this issue is approached through the notion of contextual objectivity—a response to the uncertainty of clinical reality, where patient and situational variability preclude definitive results. Thus, objectivity is better understood as the ability to interpret data critically, based on the specific context of each patient and clinical situation.

AI helps overcome this challenge through unsupervised clustering algorithms, which automatically classify COP recordings. This approach resembles Kantian logic in organizing experience, as patterns of “normality” or “instability” are not predefined by theory but emerge from the data themselves, guided by algorithms that act as operational categories. Additionally, AI facilitates the identification of outliers, which allows for the revision of auxiliary hypotheses within a Lakatosian framework. According to Lakatos, anomalies do not immediately falsify a theory's core but prompt a review of related assumptions—such as normality criteria or the relationship between clinical variables and COP data. This continuous revision reinforces the progressiveness of the posturological research program by expanding its predictive scope and explanatory power.

Integrating AI into clinical posturology also requires reformulating the training programs for posturologists. These professionals must not only understand biomechanical and neuroscientific principles but also possess the critical capacity to interpret AI-generated patterns. This requirement mirrors clinical training in medicine, where students learn to interpret variable clinical signs and adapt to individualized patient care. From the medical philosophy perspective, professional training should not be limited to standardized procedures but should include contextualized and critical education that accounts for clinical data variability.

In clinical medicine, evidence-based medicine (EBM) promotes professionals’ ability to interpret studies contextually and non-deterministically (Saborido, 2020). Similarly, posturology training should incorporate applied epistemology to help future professionals understand concepts such as variability, falsifiability, and adaptability. AI introduces a non-deterministic logic into posturological practice by detecting emergent patterns and classifying COP records. Future professionals must be capable of interpreting predictive models generated by AI and adapting them to each patient's uniqueness. This approach strengthens not only technical training but also the interdisciplinary synergy between neuroscience, informatics, and biomechanics.

Knowledge dissemination is a key pillar in legitimizing clinical posturology. Creating best practice manuals, publishing scientific articles, and participating in conferences and symposia allow for hypothesis confrontation, validation of predictive models, and the unification of stabilometric procedures. From the philosophy of medicine perspective, dissemination involves not just publishing articles but also sharing clinical protocols and guidelines, as seen in EBM. AI use in stabilometry promotes convergence among biomechanical, neuroscientific, and cybernetic approaches—illustrating the methodological pluralism advocated by Paul Feyerabend. This pluralism does not imply enforcing a single method but allows multiple approaches to interact, thereby fostering the development of more robust and legitimate knowledge. In this sense, participation in international conferences and the development of best practice manuals should be understood not as imposing rigid standards but as creating local and situated norms that consolidate posturology as an autonomous epistemic community.

The epistemological implications of research in clinical posturology extend beyond theoretical knowledge production to influence scientific practice, professional education, and academic dissemination. The integration of AI helps address issues of variability, reproducibility, and hypothesis refinement, establishing a knowledge-production framework based on uncertainty management. From the philosophy of medicine viewpoint, this aligns with the notion of contextual objectivity—understood as achieving critical objectivity in clinical data interpretation. AI facilitates pattern recognition and auxiliary hypothesis revision, following Lakatosian logic, where anomalies are handled by adjusting auxiliary assumptions. The creation of best practice manuals and participation in scholarly forums contributes to legitimizing clinical posturology as an autonomous scientific discipline, strengthening its theoretical, methodological, and epistemological framework.

This review addressed the epistemological foundations of clinical posturology, highlighting four central challenges: the definition of the object of study, the objectivity and reproducibility of measurements, theoretical interdisciplinarity, and hypothesis falsifiability. This analysis revealed that the complexity of posturology lies not only in the study of postural control but also in the construction of scientific knowledge about this discipline. Given that it is a dynamic, adaptive, and nonlinear phenomenon, knowledge production in this field requires flexible methodologies and a critical logic capable of addressing the inherent variability of stabilometric data.

A key finding was the reinterpretation of the concept of objectivity. Traditionally, objectivity was understood as the elimination of variability, but from the perspective of the philosophy of medicine, objectivity resides in the critical management of such variability. The notion of contextual objectivity is crucial for interpreting stabilometric data, where inter- and intra-subject variability is not an error but a defining characteristic of complex systems. This conception shifts the focus from eliminating uncertainty to interpreting and managing it.

The logic of falsifiability, particularly through Lakatos’ perspective, provides another valuable insight. Rather than refuting entire theories, it proposes the evaluation of auxiliary hypotheses and the adjustment of operational criteria—such as factors influencing center of pressure (COP) data, for example, foot positioning or the use of insoles. This approach underscores the importance of continuous revision in scientific research and the need to adopt methodologies that refine theoretical frameworks rather than discard them prematurely.

The integration of artificial intelligence (AI) emerges not only as a technical tool but also as an epistemological instrument. AI facilitates the detection of emergent patterns and the automatic classification of data, which aligns with Kantian logic, whereby categories do not precede experience but instead arise from empirical observations. In the context of stabilometry, this perspective enables the construction of normality and instability patterns based on data, thereby transforming validation practices and optimizing clinical interpretation. Thus, AI not only modernizes analytical tools but also reconfigures the modes of knowledge production and legitimation in posturology.

In parallel, the creation of scientific collaboration networks is essential for the consolidation of clinical posturology as an autonomous discipline. The formation of associations dedicated to this field, such as the Posturology Association of Argentina, underscores the importance of collective knowledge-building. These initiatives make it possible to coordinate efforts aimed at promoting research, disseminating scientific advancements, and establishing standards of good practice. In this sense, evidence-based medicine (EBM) provides an appropriate reference framework to guide the standardization of clinical practices, ensure the quality of interventions, and strengthen disciplinary legitimacy.

In summary, this review has explored the importance of adopting an interdisciplinary and reflective approach to address the epistemological challenges of clinical posturology. The critical management of variability, the understanding of falsifiability as a process focused on revising auxiliary hypotheses, and the adoption of tools such as AI are essential elements to strengthen knowledge production in this field. Moreover, the articulation between individual research and collective efforts through professional associations contributes to the consolidation of a solid epistemic community committed to the continuous improvement of clinical practice. These reflections not only enrich the epistemological analysis of the discipline but also provide tools to face contemporary challenges in the evaluation and treatment of postural control.

Conflict of Interest: The authors declare no conflicts of interest.

Author Contributionss:
Quintana, V. G.: Conceptualization, Formal analysis, Investigation, Methodology, Supervision, Validation, Visualization, Writing – original draft, Writing – review & editing
Amodio, E. P.: Conceptualization, Formal analysis, Investigation, Methodology, Validation, Visualization, Writing – original draft, Writing – review & editing
Gulin, M. D.: Conceptualization, Formal analysis, Investigation, Methodology, Supervision, Validation, Writing – original draft, Writing – review & editing
Casimiro-Silvera, J.: Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Writing – original draft, Writing – review & editing

Acknowledgments:
The authors would like to thank all members of the board of the Posturology Association of Argentina, as well as their colleagues at the Universidad Nacional de Hurlingham (UNAHUR), for their encouragement and support in carrying out and publishing this work.