Predictive Models for Health Deterioration: Understanding Disease Pathways for Personalized Medicine.

Artificial intelligence (AI) and machine learning (ML) methods are currently widely employed in medicine and healthcare. A PubMed search returns more than 100,000 articles on these topics published between 2018 and 2022 alone. Notwithstanding several recent reviews in various subfields of AI and ML in medicine, we have yet to see a comprehensive review around the methods' use in longitudinal analysis and prediction of an individual patient's health status within a personalized disease pathway. This review seeks to fill that gap. After an overview of the AI and ML methods employed in this field and of specific medical applications of models of this type, the review discusses the strengths and limitations of current studies and looks ahead to future strands of research in this field. We aim to enable interested readers to gain a detailed impression of the research currently available and accordingly plan future work around predictive models for deterioration in health status.

Creation of a pandemic memory by tracing COVID-19 infections and immunity in Luxembourg (CON-VINCE).

BACKGROUND: During the COVID-19 pandemic swift implementation of research cohorts was key. While many studies focused exclusively on infected individuals, population based cohorts are essential for the follow-up of SARS-CoV-2 impact on public health. Here we present the CON-VINCE cohort, estimate the point and period prevalence of the SARS-CoV-2 infection, reflect on the spread within the Luxembourgish population, examine immune responses to SARS-CoV-2 infection and vaccination, and ascertain the impact of the pandemic on population psychological wellbeing at a nationwide level. METHODS: A representative sample of the adult Luxembourgish population was enrolled. The cohort was followed-up for twelve months. SARS-CoV-2 RT-qPCR and serology were conducted at each sampling visit. The surveys included detailed epidemiological, clinical, socio-economic, and psychological data. RESULTS: One thousand eight hundred sixty-five individuals were followed over seven visits (April 2020-June 2021) with the final weighted period prevalence of SARS-CoV-2 infection of 15%. The participants had similar risks of being infected regardless of their gender, age, employment status and education level. Vaccination increased the chances of IgG-S positivity in infected individuals. Depression, anxiety, loneliness and stress levels increased at a point of study when there were strict containment measures, returning to baseline afterwards. CONCLUSION: The data collected in CON-VINCE study allowed obtaining insights into the infection spread in Luxembourg, immunity build-up and the impact of the pandemic on psychological wellbeing of the population. Moreover, the study holds great translational potential, as samples stored at the biobank, together with self-reported questionnaire information, can be exploited in further research. TRIAL REGISTRATION: Trial registration number: NCT04379297, 10 April 2020.

Which Comprehensive Geriatric Assessment (CGA) instruments are currently used in Germany: a survey.

BACKGROUND: The Comprehensive Geriatric Assessment (CGA) records geriatric syndromes in a standardized manner, allowing individualized treatment tailored to the patient's needs and resources. Its use has shown a beneficial effect on the functional outcome and survival of geriatric patients. A recently published German S1 guideline for level 2 CGA provides recommendations for the use of a broad variety of different assessment instruments for each geriatric syndrome. However, the actual use of assessment instruments in routine geriatric clinical practice and its consistency with the guideline and the current state of literature has not been investigated to date. METHODS: An online survey was developed by an expert group of geriatricians and sent to all licenced geriatricians (n = 569) within Germany. The survey included the following geriatric syndromes: motor function and self-help capability, cognition, depression, pain, dysphagia and nutrition, social status and comorbidity, pressure ulcers, language and speech, delirium, and frailty. Respondents were asked to report which geriatric assessment instruments are used to assess the respective syndromes. RESULTS: A total of 122 clinicians participated in the survey (response rate: 21%); after data cleaning, 76 data sets remained for analysis. All participants regularly used assessment instruments in the following categories: motor function, self-help capability, cognition, depression, and pain. The most frequently used instruments in these categories were the Timed Up and Go (TUG), the Barthel Index (BI), the Mini Mental State Examination (MMSE), the Geriatric Depression Scale (GDS), and the Visual Analogue Scale (VAS). Limited or heterogenous assessments are used in the following categories: delirium, frailty and social status. CONCLUSIONS: Our results show that the assessment of motor function, self-help capability, cognition, depression, pain, and dysphagia and nutrition is consistent with the recommendations of the S1 guideline for level 2 CGA. Instruments recommended for more frequent use include the Short Physical Performance Battery (SPPB), the Montreal Cognitive Assessment (MoCA), and the WHO-5 (depression). There is a particular need for standardized assessment of delirium, frailty and social status. The harmonization of assessment instruments throughout geriatric departments shall enable more effective treatment and prevention of age-related diseases and syndromes.

Blood-based biomarker in Parkinson's disease: potential for future applications in clinical research and practice.

The clinical presentation of Parkinson's disease (PD) is both complex and heterogeneous, and its precise classification often requires an intensive work-up. The differential diagnosis, assessment of disease progression, evaluation of therapeutic responses, or identification of PD subtypes frequently remains uncertain from a clinical point of view. Various tissue- and fluid-based biomarkers are currently being investigated to improve the description of PD. From a clinician's perspective, signatures from blood that are relatively easy to obtain would have great potential for use in clinical practice if they fulfill the necessary requirements as PD biomarker. In this review article, we summarize the knowledge on blood-based PD biomarkers and present both a researcher's and a clinician's perspective on recent developments and potential future applications.

Acute exercise following skill practice promotes motor memory consolidation in Parkinson's disease.

Acute cardiovascular exercise has shown to promote neuroplastic processes supporting the consolidation of newly acquired motor skills in healthy adults. First results suggest that this concept may be transferred to populations with motor and cognitive dysfunctions. In this context, Parkinson's disease (PD) is highly relevant since patients demonstrate deficits in motor learning. Hence, in the present study we sought to explore the effect of a single post-practice exercise bout on motor memory consolidation in PD. For this purpose, 17 patients with PD (Hoehn and Yahr: 1 - 2.5, age: 60.1 ± 7.9 y) practiced a whole-body skill followed by either (i) a moderate-intense bout of cycling, or (ii) seated rest for a total of 30 min. The motor skill required the participants to balance on a tiltable platform (stabilometer) for 30 s. During skill practice, participants performed 15 trials followed by a retention test 1 day and 7 days later. We calculated time in balance (platform within ± 5° from horizontal) for each trial and within- and between-group differences in memory consolidation (i.e. offline learning = skill change from last acquisition block to retention tests) were analyzed. Groups revealed similar improvements during skill practice (F4,60 = 0.316, p = 0.866), but showed differences in offline learning, which were only evident after 7 days (F1,14 = 5.602, p = 0.033). Our results suggest that a single post-practice exercise bout is effective in enhancing long-term motor memory consolidation in a population with motor learning impairments. This may point at unique promoting effects of exercise on dopamine neurotransmission involved in memory formation. Future studies should investigate the potential role of exercise-induced effects on the dopaminergic system.

Hidden Markov Model based stride segmentation on unsupervised free-living gait data in Parkinson's disease patients.

BACKGROUND: To objectively assess a patient's gait, a robust identification of stride borders is one of the first steps in inertial sensor-based mobile gait analysis pipelines. While many different methods for stride segmentation have been presented in the literature, an out-of-lab evaluation of respective algorithms on free-living gait is still missing. METHOD: To address this issue, we present a comprehensive free-living evaluation dataset, including 146.574 semi-automatic labeled strides of 28 Parkinson's Disease patients. This dataset was used to evaluate the segmentation performance of a new Hidden Markov Model (HMM) based stride segmentation approach compared to an available dynamic time warping (DTW) based method. RESULTS: The proposed HMM achieved a mean F1-score of 92.1% and outperformed the DTW approach significantly. Further analysis revealed a dependency of segmentation performance to the number of strides within respective walking bouts. Shorter bouts ([Formula: see text] strides) resulted in worse performance, which could be related to more heterogeneous gait and an increased diversity of different stride types in short free-living walking bouts. In contrast, the HMM reached F1-scores of more than 96.2% for longer bouts ([Formula: see text] strides). Furthermore, we showed that an HMM, which was trained on at-lab data only, could be transferred to a free-living context with a negligible decrease in performance. CONCLUSION: The generalizability of the proposed HMM is a promising feature, as fully labeled free-living training data might not be available for many applications. To the best of our knowledge, this is the first evaluation of stride segmentation performance on a large scale free-living dataset. Our proposed HMM-based approach was able to address the increased complexity of free-living gait data, and thus will help to enable a robust assessment of stride parameters in future free-living gait analysis applications.

Validation of a Sensor-Based Gait Analysis System with a Gold-Standard Motion Capture System in Patients with Parkinson's Disease.

Digital technologies provide the opportunity to analyze gait patterns in patients with Parkinson's Disease using wearable sensors in clinical settings and a home environment. Confirming the technical validity of inertial sensors with a 3D motion capture system is a necessary step for the clinical application of sensor-based gait analysis. Therefore, the objective of this study was to compare gait parameters measured by a mobile sensor-based gait analysis system and a motion capture system as the gold standard. Gait parameters of 37 patients were compared between both systems after performing a standardized 5 × 10 m walking test by reliability analysis using intra-class correlation and Bland-Altman plots. Additionally, gait parameters of an age-matched healthy control group (n = 14) were compared to the Parkinson cohort. Gait parameters representing bradykinesia and short steps showed excellent reliability (ICC > 0.96). Shuffling gait parameters reached ICC > 0.82. In a stridewise synchronization, no differences were observed for gait speed, stride length, stride time, relative stance and swing time (p > 0.05). In contrast, heel strike, toe off and toe clearance significantly differed between both systems (p < 0.01). Both gait analysis systems distinguish Parkinson patients from controls. Our results indicate that wearable sensors generate valid gait parameters compared to the motion capture system and can consequently be used for clinically relevant gait recordings in flexible environments.

[Care of patients with Parkinson's disease in Germany: status quo and perspectives as reflected in the digital transition]. / Versorgung von Parkinson-Patienten in Deutschland: Status quo und Perspektiven im Spiegel des digitalen Wandels.

As a chronic neurodegenerative disease, Parkinson's disease requires a close cooperation between different specialist disciplines in order to ensure the best possible quality of life for patients. A problem that has been identified is the inadequate communication between the protagonists (e.g. caregivers, physicians and therapists), especially at the sectoral interfaces. Due to structural hurdles, the current process and supply chains for Parkinson's disease do not reflect successful cross-sectoral care. Against the background of the new Digital Care Act in Germany that refunds patient-centered digital healthcare applications (DiGA), innovative, digital care and communication structures can now be established and thus comprehensively revolutionize the care of chronic diseases, such as Parkinson's disease. In this review examples and case application scenarios are presented and critically discussed.

Assessment of gait parameters and physical function in patients with advanced cancer participating in a 12-week exercise and nutrition programme: A controlled clinical trial.

OBJECTIVE: Gait is a sensitive marker for functional declines commonly seen in patients treated for advanced cancer. We tested the effect of a combined exercise and nutrition programme on gait parameters of advanced-stage cancer patients using a novel wearable gait analysis system. METHODS: Eighty patients were allocated to a control group with nutritional support or to an intervention group additionally receiving whole-body electromyostimulation (WB-EMS) training (2×/week). At baseline and after 12 weeks, physical function was assessed by a biosensor-based gait analysis during a six-minute walk test, a 30-s sit-to-stand test, a hand grip strength test, the Karnofsky Index and EORTC QLQ-C30 questionnaire. Body composition was measured by bioelectrical impedance analysis and inflammation by blood analysis. RESULTS: Final analysis included 41 patients (56.1% male; 60.0 ± 13.0 years). After 12 weeks, the WB-EMS group showed higher stride length, gait velocity (p < .05), six-minute walking distance (p < .01), bodyweight and skeletal muscle mass, and emotional functioning (p < .05) compared with controls. Correlations between changes in gait and in body composition, physical function and inflammation were detected. CONCLUSION: Whole-body electromyostimulation combined with nutrition may help to improve gait and functional status of cancer patients. Sensor-based mobile gait analysis objectively reflects patients' physical status and could support treatment decisions.

Inertial sensor-based gait parameters reflect patient-reported fatigue in multiple sclerosis.

BACKGROUND: Multiple sclerosis (MS) is a disabling disease affecting the central nervous system and consequently the whole body's functional systems resulting in different gait disorders. Fatigue is the most common symptom in MS with a prevalence of 80%. Previous research studied the relation between fatigue and gait impairment using stationary gait analysis systems and short gait tests (e.g. timed 25 ft walk). However, wearable inertial sensors providing gait data from longer and continuous gait bouts have not been used to assess the relation between fatigue and gait parameters in MS. Therefore, the aim of this study was to evaluate the association between fatigue and spatio-temporal gait parameters extracted from wearable foot-worn sensors and to predict the degree of fatigue. METHODS: Forty-nine patients with MS (32 women; 17 men; aged 41.6 years, EDSS 1.0-6.5) were included where each participant was equipped with a small Inertial Measurement Unit (IMU) on each foot. Spatio-temporal gait parameters were obtained from the 6-min walking test, and the Borg scale of perceived exertion was used to represent fatigue. Gait parameters were normalized by taking the difference of averaged gait parameters between the beginning and end of the test to eliminate inter-individual differences. Afterwards, normalized parameters were transformed to principle components that were used as input to a Random Forest regression model to formulate the relationship between gait parameters and fatigue. RESULTS: Six principal components were used as input to our model explaining more than 90% of variance within our dataset. Random Forest regression was used to predict fatigue. The model was validated using 10-fold cross validation and the mean absolute error was 1.38 points. Principal components consisting mainly of stride time, maximum toe clearance, heel strike angle, and stride length had large contributions (67%) to the predictions made by the Random Forest. CONCLUSIONS: The level of fatigue can be predicted based on spatio-temporal gait parameters obtained from an IMU based system. The results can help therapists to monitor fatigue before and after treatment and in rehabilitation programs to evaluate their efficacy. Furthermore, this can be used in home monitoring scenarios where therapists can monitor fatigue using IMUs reducing time and effort of patients and therapists.

[The history of Freezing-of-gait in Parkinson's disease - from phenomena to symptom]. / Die Geschichte des 'Freezing-of-gait' beim Parkinson-Syndrom ­ vom Phänomen zum Symptom.

The background of the freezing-of-gait (FOG) phenomenon in Parkinson's syndrome is presented in this review. The following issues are addressed: characterization of the symptom freezing and its subtypes that challenge standardized diagnostic procedures; available assessment methods generating freezing-related parameters that not only support clinical studies but can also be applied in everyday care, and current therapy options. FOG exists in different subtypes, and clinical and diagnostic definitions are limited by subjective characterization and semi-standardized tests. FOG-specific drug options are not existing, apart from the optimization of dopaminergic medication, which may also be due to the poor discriminatory power of standardized diagnostics. This is also true for deep brain stimulation. Both of these therapeutic options may be due not only to the complex neural network alterations as a motor-control correlate of FOG, but also because of challenging diagnostic assessments methodologies. Innovative, wearable, sensor-based diagnostic strategies are currently being developed, and supportive therapies using tools and technologies focusing on 'cueing' are becoming increasingly well accepted. Even though high level evidence is missing, they provide a helpful treatment option for individualized therapy. It can be assumed that these options will become particularly popular due to technological progress and likely alter the everyday treatment challenges faced by doctors and therapists.

[Recommendation for the differentiated use of nuclear medical diagnostic for parkinsonian syndromes]. / Empfehlung zum differenzierten Einsatz nuklearmedizinischer Diagnostik bei Parkinson-Syndromen.

The present work provides an overview of the various nuclear medicine methods in the diagnosis of neurodegenerative parkinsonian syndromes and their respective evidence and is intended to enable practical decision-making aids in the application and interpretation of the methods and findings. The value of the procedures differs considerably in relation to the two relevant diagnostic questions. On the one hand, it is the question of whether there is a neurodegenerative parkinsonian syndrome at all, and on the other hand the question of which one. While the DAT-SPECT is undisputedly the method of choice for answering the first question (taking certain parameters into account), this method is not suitable for answering the second question. To categorise parkinsonian syndromes into idiopathic (i. e. Parkinson´s disease) or atypical, various procedures are used in everyday clinical practice including MIBG scintigraphy, and FDG-PET. We explain why FDG-PET currently is not only the most suitable of these methods to differentiate an idiopathic parkinsonian syndrome, from an atypical Parkinson's syndrome, but also enables sufficiently valid to distinguish the various atypical neurodegenerative Parkinson's syndromes (i. e. MSA, PSP and CBD) from each other and therefore should be reimbursed by health insurances.

Neurogeriatrics-a vision for improved care and research for geriatric patients with predominating neurological disabilities.

Geriatric medicine is a rapidly evolving field that addresses diagnostic, therapeutic and care aspects of older adults. Some disabilities and disorders affecting cognition (e.g. dementia), motor function (e.g. stroke, Parkinson's disease, neuropathies), mood (e.g. depression), behavior (e.g. delirium) and chronic pain disorders are particularly frequent in old subjects. As knowledge about these age-associated conditions and disabilities is steadily increasing, the integral implementation of neurogeriatric knowledge in geriatric medicine and specific neurogeriatric research is essential to develop the field. This article discusses how neurological know-how could be integrated in academic geriatric medicine to improve care of neurogeriatric patients, to foster neurogeriatric research and training concepts and to provide innovative care concepts for geriatric patients with predominant neurological conditions and disabilities.

A roadmap for implementation of patient-centered digital outcome measures in Parkinson's disease obtained using mobile health technologies.

Obtaining reliable longitudinal information about everyday functioning from individuals with Parkinson's disease (PD) in natural environments is critical for clinical care and research. Despite advances in mobile health technologies, the implementation of digital outcome measures is hindered by a lack of consensus on the type and scope of measures, the most appropriate approach for data capture (eg, in clinic or at home), and the extraction of timely information that meets the needs of patients, clinicians, caregivers, and health care regulators. The Movement Disorder Society Task Force on Technology proposes the following objectives to facilitate the adoption of mobile health technologies: (1) identification of patient-centered and clinically relevant digital outcomes; (2) selection criteria for device combinations that offer an acceptable benefit-to-burden ratio to patients and that deliver reliable, clinically relevant insights; (3) development of an accessible, scalable, and secure platform for data integration and data analytics; and (4) agreement on a pathway for approval by regulators, adoption into e-health systems and implementation by health care organizations. We have developed a tentative roadmap that addresses these needs by providing the following deliverables: (1) results and interpretation of an online survey to define patient-relevant endpoints, (2) agreement on the selection criteria for use of device combinations, (3) an example of an open-source platform for integrating mobile health technology output, and (4) recommendations for assessing readiness for deployment of promising devices and algorithms suitable for regulatory approval. This concrete implementation guidance, harmonizing the collaborative endeavor among stakeholders, can improve assessments of individuals with PD, tailor symptomatic therapy, and enhance health care outcomes. © 2019 International Parkinson and Movement Disorder Society.

Interindividual Balance Adaptations in Response to Perturbation Treadmill Training in Persons With Parkinson Disease.

BACKGROUND AND PURPOSE: Perturbation training is a promising approach to reduce fall incidence in persons with Parkinson disease (PwPD). This study aimed to evaluate interindividual differences in balance adaptations in response to perturbation treadmill training (PTT) and identify potential outcome predictors. METHODS: PwPD (n = 43, Hoehn & Yahr stage 1-3.5) were randomly assigned to either 8 weeks of PTT or conventional treadmill training (CTT) without perturbations. At baseline and following intervention, data from 4 domains of balance function (reactive, anticipatory, dynamic postural control, and quiet stance) were collected. Using responder analysis we investigated interindividual differences (responder rates and magnitude of change) and potential predictive factors. RESULTS: PTT showed a significantly higher responder rate in the Mini Balance Evaluation Systems Test (Mini-BESTest) subscore reactive postural control, compared with CTT (PTT = 44%; CTT = 10%; risk ratio = 4.22, confidence interval = 1.03-17.28). Additionally, while between-groups differences were not significant, the proportion of responders in the measures of dynamic postural control was higher for PTT compared with CTT (PTT: 22%-39%; CTT: 5%-10%). The magnitude of change in responders and nonresponders was similar in both groups. PTT responders showed significantly lower initial balance performance (4/8 measures) and cognitive function (3/8 measures), and were older and at a more advanced disease stage, based on descriptive evaluation. DISCUSSION AND CONCLUSIONS: Our findings suggest that PTT is beneficial to improve reactive balance in PwPD. Further, PTT appeared to be effective only for a part of PwPD, especially for those with lower balance and cognitive function, which needs further attention.Video Abstract available for more insights from the authors (see the Video, Supplemental Digital Content 1, http://links.lww.com/JNPT/A1).

Correction to: Development and clinical validation of inertial sensor-based gait-clustering methods in Parkinson's disease.

The original article [1] contained an error whereby Fig. 6 contained a minor shading glitch affecting its presentation. This has now been corrected.

Development and clinical validation of inertial sensor-based gait-clustering methods in Parkinson's disease.

BACKGROUND: Gait symptoms and balance impairment are characteristic indicators for the progression in Parkinson's disease (PD). Current gait assessments mostly focus on straight strides with assumed constant velocity, while acceleration/deceleration and turning strides are often ignored. This is either due to the set up of typical clinical assessments or technical limitations in capture volume. Wearable inertial measurement units are a promising and unobtrusive technology to overcome these limitations. Other gait phases such as initiation, termination, transitioning (between straight walking and turning) and turning might be relevant as well for the evaluation of gait and balance impairments in PD. METHOD: In a cohort of 119 PD patients, we applied unsupervised algorithms to find different gait clusters which potentially include the clinically relevant information from distinct gait phases in the standardized 4x10 m gait test. To clinically validate our approach, we determined the discriminative power in each gait cluster to classify between impaired and unimpaired PD patients and compared it to baseline (analyzing all straight strides). RESULTS: As a main result, analyzing only one of the gait clusters constant, non-constant or turning led in each case to a better classification performance in comparison to the baseline (increase of area under the curve (AUC) up to 19% relative to baseline). Furthermore, gait parameters (for turning, constant and non-constant gait) that best predict motor impairment in PD were identified. CONCLUSIONS: We conclude that a more detailed analysis in terms of different gait clusters of standardized gait tests such as the 4x10 m walk may give more insights about the clinically relevant motor impairment in PD patients.

Turning Analysis during Standardized Test Using On-Shoe Wearable Sensors in Parkinson's Disease.

Mobile gait analysis systems using wearable sensors have the potential to analyze and monitor pathological gait in a finer scale than ever before. A closer look at gait in Parkinson's disease (PD) reveals that turning has its own characteristics and requires its own analysis. The goal of this paper is to present a system with on-shoe wearable sensors in order to analyze the abnormalities of turning in a standardized gait test for PD. We investigated turning abnormalities in a large cohort of 108 PD patients and 42 age-matched controls. We quantified turning through several spatio-temporal parameters. Analysis of turn-derived parameters revealed differences of turn-related gait impairment in relation to different disease stages and motor impairment. Our findings confirm and extend the results from previous studies and show the applicability of our system in turning analysis. Our system can provide insight into the turning in PD and be used as a complement for physicians' gait assessment and to monitor patients in their daily environment.

[Wearables in the treatment of neurological diseases-where do we stand today?] / "Wearables" in der Behandlung neurologischer Erkrankungen ­ wo stehen wir heute?

Fitness and lifestyle trackers raise the awareness for wearable sensors in medical applications for clinical trials and healthcare. Various functional impairments of patients with neurological diseases are an ideal target to generate wearable-derived and patient-centered parameters that have the potential to support prevention, prediction, diagnostic procedures and therapy monitoring during the clinical work-up; however, substantial differences between clinical grade wearables and fitness trackers have to be acknowledged. For the application in clinical trials or individualized patient care distinct technical and clinical validation trials have to be conducted. The different test environments under laboratory conditions during standardized tests or under unsupervised home monitoring conditions have to be included in the algorithmic processing of sensor raw data in order to enable a clinical decision support under real-life conditions. This article presents the general understanding of the technical application for the most relevant functional impairments in neurology. While wearables used for sleep assessment have already reached a high level of technological readiness due to the defined test environment (bed, sleep), other wearable applications, e.g. for gait and mobility during home monitoring require further research in order to transfer the technical capabilities into real-life patient care.

Balance and mobility in geriatric patients : Assessment and treatment of neurological aspects.

BACKGROUND: Personal autonomy in advanced age critically depends on mobility in the environment. Geriatric patients are often not able to walk safely with sufficient velocity. In many cases, multiple factors contribute to the deficit. Diagnostic identification of single components enables a specific treatment. OBJECTIVE: This article describes the most common neurological causes of imbalance and impaired gait that are relevant for a pragmatic approach for the assessment of deficits in clinical and natural environments taking into account the physiology of balance and gait control, typical morbidities in older people and the potential of innovative assessment technologies. MATERIAL AND METHODS: Expert opinion based on a narrative review of the literature and with reference to selected research topics. RESULTS AND DISCUSSION: Common neurological causes of impaired balance and mobility are sensory deficits (reduced vision, peripheral neuropathy, vestibulopathy), neurodegeneration in disorders with an impact on movement control and motoric functions (Parkinsonian syndromes, cerebellar ataxia, vascular encephalopathy) and functional (psychogenic) disorders, particularly a fear of falling. Clinical tests and scores in laboratory environments are complemented by the assessment in the natural environment. Wearable sensors, mobile smartphone-based assessment of symptoms and functions and adopted strategies for analysis are currently emerging. Use of these data enables a personalized treatment. Furthermore, sensor-based assessment ensures that effects are measured objectively.