DR.BEAT: Initial Functional Testing of a BCG Wearable Prototype for Recording Ballistocardiographic Signals

DR.BEAT ("Digital Research on Ballistocardiography for Extraterrestrial And Terrestrial use") develops a miniaturized sensor system with signal processing to interpret ballistocardiographic signals and implements an application oriented user interface. Presented is a breadboard prototype's functional tests with regard to data completeness and plausibility. The analysis confirmed a reliability of 99.99995% over the tests and the signals displayed the expected heart-specific characteristics. These results support the ethical justifiability of an initial study.

Towards a Recommendation for Good Health Data Modeling (GHDM) - Results of Expert Interviews

Appropriate data models are essential for the systematic collection, aggregation, and integration of health data and for subsequent analysis. However, recommendations for modeling health data are often not publicly available within specific projects. Therefore, the project Zukunftslabor Gesundheit investigates recommendations for modeling. Expert interviews with five experts were conducted and analyzed using qualitative content analysis. Based on the condensed categories "governance", "modeling" and "standards", the project team generated eight hypotheses for recommendations on health data modeling. In addition, relevant framework conditions such as different roles, international cooperation, education/training and political influence were identified. Although emerging from interviewing a small convenience sample of experts, the results help to plan more extensive data collections and to create recommendations for health data modeling.

DR.BEAT: First Insights into a Study to Collect Baseline BCG Data with a Sensor-Based Wearable Prototype in Heart-Healthy Adults

The DR.BEAT project aims at the further development of a measurement system for recording ballistocardiographic signals into a body-worn sensor system combined with extensive signal processing, data evaluation and visualization. With a first breadboard prototype, an explorative feasibility study for acquiring initial signals of healthy cardiac activity in adults was performed. This paper briefly presents the DR.BEAT project, the breadboard prototype, the study conducted, and initial insights into the study results. The signals obtained in the study exhibit the seismocardiographic characteristics as reported in the literature and form the basis for further development of the hardware as well as the pre-processing and automated analysis algorithms in the DR.BEAT project.Clinical Relevance- The characteristics of ballisto- and seismocardiographic signals allow to infer about the mechanical work of the heart. The development of a body-worn sensor system to record ballisto- and seismocardiographic signals, compact enough for everyday wear, enables the acquisition of heart-specific parameters in terrestrial as well as extraterrestrial application scenarios. Combined with extensive signal analysis and visualization, it holds the potential to monitor heart health in a variety of contexts and support its maintenance and improvement.

[Health enabling technologies and intelligent environments in rehabilitation]

BACKGROUND

The increasing digitalization of society is having an impact on medicine. People increasingly use digital devices and services for various purposes (e.g., sports, security, convenience). Ubiquity, a strong degree of connectivity and high context sensitivity are creating intelligent environments that generate data about individuals. Suitable evaluation algorithms can extract information about the personal health status that can be used for diagnostics and treatment. Gamification methods allow patients to be more actively involved in their recovery, which can have a positive effect on adherence. Particularly in the field of rehabilitation medicine, which often affects and interacts with the personal living environment, the use of this information can make a difference.

OBJECTIVE

Using specific examples of the application of assistive health technologies and intelligent environments in rehabilitation medicine, the current state of development is presented and the possible future research directions and needs for action in this field are presented in a practical way.

MATERIAL AND METHODS

Three exemplary research projects introduce the topic, are embedded in the current state of research and allow a projection into the future against the background of many years of experience.

RESULTS

The reported projects show not only the technical feasibility but also individually the medical effectiveness of interventions.

CONCLUSION

Finally, an analysis of the barriers that have so far prevented a more intensive use of the technologies and how these might be countered is carried out.

Compiling Criteria for Assessing Essential Aspects of Home Exercise Performance: A Questionnaire-Based Approach

Health-enabling technologies (HET) have high potential in rehabilitation to support patients performing their home exercises. The modeling of human movements as well as the modelling of quality criteria of an exercise performance remains challenging when implementing HETs. A combination of data-driven approaches and knowledge-based methods may deliver new insights. This requires structured quality assessments of concrete exercise performances from a therapists' point of view. Therefore, a structured, easy to use questionnaire to assess home exercise performances is developed and implemented. The questionnaire consists of eight items in three categories: (1-4) overall assessment of quality and quantity, (5-7) need for correction, and (8) correction hints. The collected data will be the basis for mathematical modeling of home exercise performance assessment as foundation for the development of patient supporting HETs.

Factors for Individualization of Therapeutic Exercises for the Design of Health-Enabling Technologies

Designing health-enabling technologies (HETs) to support individualized physiotherapeutic exercises requires comprehensive knowledge of bio-psycho-social factors to be considered. Therefore, this review identified factors for individualization of therapeutic exercises in patients with musculoskeletal shoulder disorders in peer-reviewed articles searched in MEDLINE. The final full-text analysis included 16 of 335 search results and extracted nineteen main categories of individualization factors. The most frequently identified main categories include progression of exercises, exercise framework, and assessment. An iterative approach with constant reassessments represents the key principle for the process of individualization. Categories that are difficult to standardize were rarely mentioned, but should also be considered. The identified factors can improve the design-process of HETs by sensitizing developers, enable further formal modelling, and support communication between developers, physiotherapists, and patients.

OnTARi: an ontology for factors influencing therapy adherence to rehabilitation

BACKGROUND

Adherence and motivation are key factors for successful treatment of patients with chronic diseases, especially in long-term care processes like rehabilitation. However, only a few patients achieve good treatment adherence. The causes are manifold. Adherence-influencing factors vary depending on indications, therapies, and individuals. Positive and negative effects are rarely confirmed or even contradictory. An ontology seems to be convenient to represent existing knowledge in this domain and to make it available for information retrieval.

METHODS

First, a manual data extraction of current knowledge in the domain of treatment adherence in rehabilitation was conducted. Data was retrieved from various sources, including basic literature, scientific publications, and health behavior models. Second, all adherence and motivation factors identified were formalized according to the ontology development methodology METHONTOLOGY. This comprises the specification, conceptualization, formalization, and implementation of the ontology "Ontology for factors influencing therapy adherence to rehabilitation" (OnTARi) in Protégé. A taxonomy-oriented evaluation was conducted by two domain experts.

RESULTS

OnTARi includes 281 classes implemented in ontology web language, ten object properties, 22 data properties, 1440 logical axioms, 244 individuals, and 1023 annotations. Six higher-level classes are differentiated: (1) Adherence, (2) AdherenceFactors, (3) AdherenceFactorCategory, (4) Rehabilitation, (5) RehabilitationForm, and (6) RehabilitationType. By means of the class AdherenceFactors 227 adherence factors, thereof 49 hard factors, are represented. Each factor involves a proper description, synonyms, possibly existing acronyms, and a German translation. OnTARi illustrates links between adherence factors through 160 influences-relations. Description logic queries implemented in Protégé allow multiple targeted requests, e.g., for the extraction of adherence factors in a specific rehabilitation area.

CONCLUSIONS

With OnTARi, a generic reference model was built to represent potential adherence and motivation factors and their interrelations in rehabilitation of patients with chronic diseases. In terms of information retrieval, this formalization can serve as a basis for implementation and adaptation of conventional rehabilitative measures, taking into account (patient-specific) adherence factors. OnTARi also enables the development of medical assistance systems to increase motivation and adherence in rehabilitation processes.

Health-Enabling Technologies to Assist Patients With Musculoskeletal Shoulder Disorders When Exercising at Home: Scoping Review

Background

Health-enabling technologies (HETs) are information and communication technologies that promote individual health and well-being. An important application of HETs is telerehabilitation for patients with musculoskeletal shoulder disorders. Currently, there is no overview of HETs that assist patients with musculoskeletal shoulder disorders when exercising at home.

Objective

This scoping review provides a broad overview of HETs that assist patients with musculoskeletal shoulder disorders when exercising at home. It focuses on concepts and components of HETs, exercise program strategies, development phases, and reported outcomes.

Methods

The search strategy used Medical Subject Headings and text words related to the terms upper extremity, exercises, and information and communication technologies. The MEDLINE, Embase, IEEE Xplore, CINAHL, PEDro, and Scopus databases were searched. Two reviewers independently screened titles and abstracts and then full texts against predefined inclusion and exclusion criteria. A systematic narrative synthesis was performed. Overall, 8988 records published between 1997 and 2019 were screened. Finally, 70 articles introducing 56 HETs were included.

Results

Identified HETs range from simple videoconferencing systems to mobile apps with video instructions to complex sensor-based technologies. Various software, sensor hardware, and hardware for output are in use. The most common hardware for output are PC displays (in 34 HETs). Microsoft Kinect cameras in connection with related software are frequently used as sensor hardware (in 27 HETs). The identified HETs provide direct or indirect instruction, monitoring, correction, assessment, information, or a reminder to exercise. Common parameters for exercise instructions are a patient’s range of motion (in 43 HETs), starting and final position (in 32 HETs), and exercise intensity (in 20 HETs). In total, 48 HETs provide visual instructions for the exercises; 29 HETs report on telerehabilitation aspects; 34 HETs only report on prototypes; and 15 HETs are evaluated for technical feasibility, acceptance, or usability, using different assessment instruments. Efficacy or effectiveness is demonstrated for only 8 HETs. In total, 18 articles report on patients’ evaluations. An interdisciplinary contribution to the development of technologies is found in 17 HETs.

Conclusions

There are various HETs, ranging from simple videoconferencing systems to complex sensor-based technologies for telerehabilitation, that assist patients with musculoskeletal shoulder disorders when exercising at home. Most HETs are not ready for practical use. Comparability is complicated by varying prototype status, different measurement instruments, missing telerehabilitation aspects, and few efficacy studies. Consequently, choosing an HET for daily use is difficult for health care professionals and decision makers. Prototype testing, usability, and acceptance tests with the later target group under real-life conditions as well as efficacy or effectiveness studies with patient-relevant core outcomes for every promising HET are required. Furthermore, health care professionals and patients should be more involved in the product design cycle to consider relevant practical aspects.

AGT-Reha-WK study: protocol for a non-inferiority trial comparing the efficacy and costs of home-based telerehabilitation for shoulder diseases with medical exercise therapy

INTRODUCTION

Shoulder lesions rank among the top 15 diagnoses accounting for days of incapacity to work. Inpatient or full-day outpatient rehabilitation are some of the standard therapies. For sustainable rehabilitation, continuation of rehabilitation after discharge from a rehabilitation centre is vital. Besides medical exercise therapy (MET), home-based physical exercise programmes are used. To monitor exercise quantity and quality, AGT-Reha, a health-enabling technology for home rehabilitation, has been developed and evaluated in a pilot study for technical feasibility and acceptance. To integrate the digital therapeutic AGT-Reha into regular healthcare processes, an efficacy evaluation is required.

METHODS AND ANALYSIS

AGT-Reha-WK is a prospective, monocentric, non-randomised, unblinded non-inferiority trial. Primary objective is to investigate whether AGT-Reha enhanced home-based exercise training is non-inferior to MET as standard aftercare. Secondary objective is to compare the costs of both therapies. Efficacy as medical success (primary outcome) is examined with regard to ability to work, return to work and sustainability of training (secondary outcomes). The outcome measure for non-inferiority is shoulder function (pain and disability) assessed by the standardised Shoulder Pain and Disability Index (SPADI). The non-inferiority margin is set to 10 points on SPADI score using a 95% CI. Subjects will be recruited at the Rehabilitation Center Bad Pyrmont, Germany. The total number of subjects should be 84 (42 per group). Treatment takes 6 months per patient. Subjects will be assessed at four time points: pre-baseline (admission to rehabilitation centre), baseline (discharge from rehabilitation centre), post-therapy and follow-up (3 months post-therapy).

ETHICS AND DISSEMINATION

Ethics approval was granted by the Ethics Committee of Hannover Medical School (ethics approval no: 7313). Results of the trial are planned to be published in a peer-reviewed journal.

TRIAL REGISTRATION NUMBER

German Clinical Trials Register DRKS00011596. Registered 2 June 2017. Recruitment started on 3 March 2017, and it is expected to continue until December 2020.

PROTOCOL VERSION

V2.0, 23 May 2018, Amendment 01: improved risk analysis, clarification of exclusion criteria to increase reproducibility, additional documentation with OpenClinica; these changes have no effect on structural equality.

Gamification in Rehabilitation of Patients With Musculoskeletal Diseases of the Shoulder: Scoping Review

Background

Gamification has become increasingly important both in research and in practice. Particularly in long-term care processes, such as rehabilitation, playful concepts are gaining in importance to increase motivation and adherence. In addition to neurological diseases, this also affects the treatment of patients with musculoskeletal diseases such as shoulder disorders. Although it would be important to assist patients during more than one rehabilitation phase, it is hypothesized that existing systems only support a single phase. It is also unclear which game design elements are currently used in this context and how they are combined to achieve optimal positive effects on motivation.

Objective

This scoping review aims to identify and analyze information and communication technologies that use game design elements to support the rehabilitation processes of patients with musculoskeletal diseases of the shoulder. The state of the art with regard to fields of application, game design elements, and motivation concepts will be determined.

Methods

We conducted a scoping review to identify relevant application systems. The search was performed in 3 literature databases: PubMed, IEEE Xplore, and Scopus. Following the PICO (population, intervention, comparison, outcome) framework, keywords and Medical Subject Headings for shoulder, rehabilitation, and gamification were derived to define a suitable search term. Two independent reviewers, a physical therapist and a medical informatician, completed the search as specified by the search strategy. There was no restriction on year of publication. Data synthesis was done by deductive-inductive coding based on qualitative content analysis.

Results

A total of 1994 articles were screened; 31 articles in English, published between 2006 and 2019, were included. Within, 27 application systems that support patients with musculoskeletal diseases of the shoulder in exercising, usually at home but also in inpatient or outpatient rehabilitation clinics, were described. Only 2 application systems carried out monitoring of adherence. Almost all were based on in-house developed software. The most frequently used game components were points, tasks, and avatars. More complex game components, such as collections and teams, were rarely used. When selecting game components, patient-specific characteristics, such as age and gender, were only considered in 2 application systems. Most were described as motivating, though an evaluation of motivational effects was usually not conducted.

Conclusions

There are only a few application systems supporting patients with musculoskeletal diseases of the shoulder in rehabilitation by using game design elements. Almost all application systems are exergames for supporting self-exercising. Application systems for multiple rehabilitation phases seem to be nonexistent. It is also evident that only a few complex game design elements are used. Patient-specific characteristic are generally neglected when selecting and implementing game components. Consequently, a holistic approach to enhance adherence to rehabilitation is required supporting patients during the entire rehabilitation process by providing motivational game design elements based on patient-specific characteristics.

Health-Enabling Technologies for Telerehabilitation of the Shoulder: A Feasibility and User Acceptance Study

Background  After discharge from a rehabilitation center the continuation of therapy is necessary to secure already achieved healing progress and sustain (re-)integration into working life. To this end, home-based exercise programs are frequently prescribed. However, many patients do not perform their exercises as frequently as prescribed or even with incorrect movements. The telerehabilitation system AGT-Reha was developed to support patients with shoulder diseases during their home-based aftercare rehabilitation.

Objectives  The presented pilot study AGT-Reha-P2 evaluates the technical feasibility and user acceptance of the home-based telerehabilitation system AGT-Reha.

Methods  A nonblinded, nonrandomized exploratory feasibility study was conducted over a 2-year period in patients' homes. Twelve patients completed a 3-month telerehabilitation exercise program with AGT-Reha. Primary outcome measures are the satisfying technical functionality and user acceptance assessed by technical parameters, structured interviews, and a four-dimensional questionnaire. Secondary endpoints are the medical rehabilitation success measured by the active range of motion and the shoulder function (pain and disability) assessed by employing the Neutral-0 Method and the standardized questionnaire “Shoulder Pain and Disability Index” (SPADI), respectively. To prepare an efficacy trial, various standardized questionnaires were included in the study to measure ability to work, capacity to work, and subjective prognosis of work capacity. The participants have been assessed at three measurement points: prebaseline (admission to rehabilitation center), baseline (discharge from rehabilitation center), and posttherapy.

Results  Six participants used the first version of AGT-Reha, while six other patients used an improved version. Despite minor technical problems, all participants successfully trained on their own with AGT-Reha at home. On average, participants trained at least once per day during their training period. Five of the 12 participants showed clinically relevant improvements of shoulder function (improved SPADI score > 11). The work-related parameters suggested a positive impact. All participants would recommend the system, ten participants would likely reuse it, and seven participants would have wanted to continue their use after 3 months.

Conclusion  The findings show that home-based training with AGT-Reha is feasible and well accepted. Outcomes of SPADI indicate the effectiveness of aftercare with AGT-Reha. A controlled clinical trial to test this hypothesis will be conducted with a larger number of participants.

Transfer Physical Therapists Knowledge: A Pre-Test to Minimize the Complexity of Physical Therapists' Quality Assessment of Shoulder Exercise Performance

Exercise therapy aims to restore normal musculoskeletal function or to reduce pain in patients with musculoskeletal shoulder disorders. Especially during long-term treatments, patients perform unsupervised exercises at home. Harmful movement deviations should be identified and avoided. Assistive technologies based on physical therapists' knowledge can support patients. In this paper, we present our approach to minimize the complexity of a physical therapists' quality assessment of a shoulder exercise performance. Four experienced physical therapists assessed the quality of 13 exercise performances shown as video recordings with a visual analogue scale and explained their ratings as free text. In some cases, the resulting assessments differed widely depending on the respective therapeutic goals. The therapists had difficulties to reduce the performances quality to a single value. Despite the existing consensus on exercises' descriptions, a more than one-dimensional scale is needed to evaluate exercises. Therefore, rating categories have to be identified for more detailed assessments.

First Feasibility Analysis of Ballistocardiography on a Passenger Flight

The project SCARAB2 (Scalable, Robust and Adaptive on Board Ballistocardiography) aims to use Ballistocardiography (BCG) to monitor flight passengers. In order to show that recorded BCG data from flights give evaluable information even in the noisy environment of an airplane, we monitored a heart-healthy passenger using BCG. Furthermore, we show that there can be a conclusion to heart activities from the recorded ballistocardiogram by comparing the data to a concurrently recorded electrocardiogram (ECG).

Wireless Sensor Network for Fall Prevention on Geriatric Wards: A Report

With regard to the growing number of older adults, it needs smart solutions for fall prevention. Especially at geriatric institutions, the risk of falling is very high and frequently leads to injuries, resulting in serious consequences. We present the Inexpensive Node for Bed Exit Detection (INBED), a comprehensive signaling system for fall prevention. The INBED system is based on a wireless sensor network infrastructure via IEEE802.15.4 and highly-specialized open hardware in-house developed wearable. The device, which will be attached to the patients, can detect several types of movement. Occurring events are forwarded to the nursing staff immediately by using the self-organizing and scalable network including wide area network integration. The system can help to relieve the staff while the personal freedom of movement and privacy of patients is increased. With this development, the energy-efficient, simple and intuitive mechanisms of proximity communication can be combined with broadband benefits.

A Vision Utilizing Gamification to Enhance Patients' with Chronic Shoulder Diseases Adherence to Rehabilitation

Although adherence is a key factor for successful treatment of chronic diseases, only about 50% of patients achieve good adherence. However, health enabling technologies and gamification offer new possibilities to enhance patient's motivation. In physical rehabilitation, various applications exist. As these often stress a specific part of the rehabilitation process, we introduce a six-step new holistic approach to apply game design elements in the entire rehabilitation process, while focusing on patients with musculoskeletal diseases of the shoulder.

INBED: A Highly Specialized System for Bed-Exit-Detection and Fall Prevention on a Geriatric Ward

OBJECTIVE

In geriatric institutions, the risk of falling of patients is very high and frequently leads to fractures of the femoral neck, which can result in serious consequences and medical costs. With regard to the current numbers of elderly people, the need for smart solutions for the prevention of falls in clinical environments as well as in everyday life has been evolving.

METHODS

Hence, in this paper, we present the Inexpensive Node for bed-exit Detection (INBED), a comprehensive, favourable signaling system for bed-exit detection and fall prevention, to support the clinical efforts in terms of fall reduction. The tough requirements for such a system in clinical environments were gathered in close cooperation with geriatricians.

RESULTS

The conceptional efforts led to a multi-component system with a core wearable device, attached to the patients, to detect several types of movements such as rising, restlessness and-in the worst case-falling. Occurring events are forwarded to the nursing staff immediately by using a modular, self-organizing and dependable wireless infrastructure. Both, the hardware and software of the entire INBED system as well as the particular design process are discussed in detail. Moreover, a trail test of the system is presented.

CONCLUSIONS

The INBED system can help to relieve the nursing staff significantly while the personal freedom of movement and the privacy of patients is increased compared to similar systems.

Leveraging Aging in Place Through Sensor-Enhanced In-Home Monitoring

Seniors expect to age in place, which means living in their own homes as long as possible with familiar facilities and environments. Due to the capability of continuous and unobtrusive monitoring, the sensor-enhanced in-ho monitoring is regarded as a promising solution to support aging in place. In this paper, by reviewing three influential projects in this field of in-home monitoring for aging in place, we present our opinions and suggestions on the development of informatics-supported aging in place for its practical application in healthcare such as diagnosis and nursing in the era of data science. To promote the practical usage of in-home monitoring in aging, we highlight the gap between demands and available approaches. We conclude that in the next stage we should design demand-oriented system, conduct evidence-based research and accelerate interdisciplinary collaboration.

Automatic Detection of Depression by Using a Neural Network

Depression is the most common psychiatric disorder worldwide, which affects more than 300 million people. We aimed to detect depressed patients and healthy people automatically. We work on the PHQ-9 questionnaires and reduced it to a PHQ-5 questionnaires with a new cut-off value of 8 to detect depressed patients. We trained a Neural Network with 70% of our dataset. Then, the proposed classifier was tested with two datasets. The first one consists of 30% of PHQ-5 datasets, which could achieve 85.69%, 99.11% and 90.56% for accuracy, sensitivity and specificity respectively. The second test dataset consists of physical patient's parameters which recorded during a study in the Hanover Medical School. This classifier has shown good results in the detection of depression based on these two datasets.

Advantages of Modular Hybrid Network Communication on Clinical Wards

The ever-increasing flood of information, especially in the medical-clinical field, inter alia due to the increase of data-intensive mobile/wearable devices, is one of the biggest challenges of medical informatics. In this work different possibilities of the integration of wearable devices on the example of the development of a fall prevention system are presented and classified. We started with a commercial off-the-shelf one-on-one system (Shimmer/Arduino) using a Bluetooth connection, integrated via nurse call system as Human-Machine-Interface. During the evaluation of the system we mentioned several new requirements and optimization possibilities. Thus, we adjusted the hardware-software-system; the near-field communication was realized by IEEE802.15.4, we replaced commercial off-the-shelf devices with highly-specialized open hardware in-house developments and we transferred the nurse call integration by setting up our own network and integrating this into an existing (wireless) local area network. With this development, the energy-efficient, simple and intuitive mechanisms of proximity communication via IEEE802.15.4 can be combined with the benefits broadband functionalities, e.g. of Wi-Fi, with both worlds benefits and the compensation of some disadvantages.

Semi-Automatically Measuring Shoulders' Range of Motion - Objective Measurements with Good Reliability and Accuracy

The shoulder's range of motion (ROM) is an important measurement for the diagnostic process and course of treatment for patients with shoulder disorders or injuries. Visual estimation to assess a shoulder's ROM is a fast measuring method, and therefore routinely used in clinical practice. Studies already proved this method as very subjective and unreliable. Misestimating the severity of a patient's disability can lead to improper treatment and should be avoided. Modern technology may help measuring the ROM more reliable, objective, non-invasive and still fast. In this paper we present a computer-based prototype to semi-automatically assess the patient's shoulder ROM. Still photography is one of the most accurate ways to determine the extent to which a shoulder can be moved. Thus, a marker-less motion sensing device is used to capture movements of patient. A study with n=9 healthy adults was conducted to validate the results of the computer-based system against a physician using goniometry. The results show great potential of this technique for abduction, adduction, anteversion and retroversion with an intraclass correlation coefficient ranging between 0.77 and 0.86 for the best measuring method. Using the system would enhance daily practice. Patients could measure their ROM during their waiting time in advance to the visit, optionally supported by a nurse. Due to the more reliable and objective result the physician can instantly start diagnosing the patient or discussing therapy options. Time for investigation is saved and more time to treat the patient with objective and reliable measurement results would be available.

Should Degree Programs in Biomedical and Health Informatics be Dedicated or Integrated? : Reflections and Recommendations after more than 40 Years of Medical Informatics Education at TU Braunschweig, including 10 Years of B.Sc. and 15 Years of M.Sc. Integrated Degree Curricula

Education in biomedical and health informatics (BMHI) has been established in many countries throughout the world. For degree programs in BMHI we can distinguish between those that are completely stand-alone or dedicated to the discipline vs. those that are integrated within another program. After running integrated degree medical informatics programs at TU Braunschweig for 10 years at the B.Sc. and for 15 years at the M.Sc level, we (1) report about this educational approach, (2) analyze recommendations on, implementations of, and experiences with degree educational programs in BMHI worldwide, (3) summarize our lessons learned with the integrated approach at TU Braunschweig, and (4) suggest an answer to the question, whether degree programs in biomedical and health informatics should be dedicated or integrated. According to our experience at TU Braunschweig and based on our analysis of publications, there is a clear dominance of dedicated degree programs in BMHI. The specialization in medical informatics within a computer science program, as offered at TU Braunschweig, may be a good way of implementing an integrated, informatics-based approach to medical informatics, in particular if a dual degree option can be chosen. The option of curricula leading to double degrees, i.e. in this case to two separate degrees in computer science and in medical informatics might, however, be a better solution.

On Methodological and Technological Challenges for Proactive Health Management in Smart Homes

Health management in smart homes has advanced during the last years. With proactive health management in such environments further progress for health prevention and care is to be expected. Challenges for proactive health management in three areas are summarized and briefly discussed: pattern recognition and machine learning, information privacy and user-oriented design, and sensor-enhanced health information systems architectures.

Introducing a Method for Transformation of Paper-Based Research Data into Concept-Based Representation with openEHR

Combining research data and clinical routine data is a chance for medical research. We present our method for the transformation of paper-based research data into a concept-based representation. With this representation the study data from research projects can be combined with data from clinical tools with less integration effort. We applied and verified our method using data from a current research study. In this paper we also show our main challenges and lessons learned. Clinical assessment data and study diaries from a long term study (n=24, 3 months observation time each, 17 different clinical assessments) stored on paper were used as the data set. An openEHR-based electronical health record platform was adapted for acquisition and representation of the research data. To avoid transcription errors, the data was entered twice by different student assistants. A third compared and corrected both data sets. Content models (17 archetypes and five templates from openEHR concept) based on clinical assessments were created manually. Web forms for data entry were created automatically on the basis of this concept-based content models. Additionally, form functionalities to support data entry and comparison were implemented. In total, 829 compositions were entered by the student assistants. With our developed method, we are able to represent the study data in a clinical concept-based platform, which means less integration effort for access and processing of research and clinical data. Some minor difficulties occurred during the process. All in all, adapting routine tools, like the EHR platform, seems to be convenient to deal with research data.

Challenges and Opportunities for Harmonizing Research Methodology: Raw Accelerometry

OBJECTIVES

Raw accelerometry is increasingly being used in physical activity research, but diversity in sensor design, attachment and signal processing challenges the comparability of research results. Therefore, efforts are needed to harmonize the methodology. In this article we reflect on how increased methodological harmonization may be achieved.

METHODS

The authors of this work convened for a two-day workshop (March 2014) themed on methodological harmonization of raw accelerometry. The discussions at the workshop were used as a basis for this review.

RESULTS

Key stakeholders were identified as manufacturers, method developers, method users (application), publishers, and funders. To facilitate methodological harmonization in raw accelerometry the following action points were proposed: i) Manufacturers are encouraged to provide a detailed specification of their sensors, ii) Each fundamental step of algorithms for processing raw accelerometer data should be documented, and ideally also motivated, to facilitate interpretation and discussion, iii) Algorithm developers and method users should be open about uncertainties in the description of data and the uncertainty of the inference itself, iv) All new algorithms which are pitched as "ready for implementation" should be shared with the community to facilitate replication and ongoing evaluation by independent groups, and v) A dynamic interaction between method stakeholders should be encouraged to facilitate a well-informed harmonization process.

CONCLUSIONS

The workshop led to the identification of a number of opportunities for harmonizing methodological practice. The discussion as well as the practical checklists proposed in this review should provide guidance for stakeholders on how to contribute to increased harmonization.

Facilitating Inter-Domain Synergies in Ambient Assisted Living Environments

Current Ambient Assisted Living (AAL) environments lack integration of sensors and actuators of other sub-domains. Creating technical and organizational integration is addressed by the BASIS project (Build Automation by a Scalable and Intelligent System), which aims to build a cross-domain home bus system. The main objective of this paper is to present an overview of design, architecture and state of realization of BASIS by describing the requirements development process, underlying hardware design and software architecture. We built a distributed system of one independent building manager with several redundantly meshed segment controllers, each controlling a bus segment with any number of bus nodes. The software system layer is divided into logical partitions representing each sub-domain. Structured data storage is possible with a special FHIR based home centered data warehouse. The system has been implemented in six apartments running under daily living conditions. BASIS integrates a broad range of sub-domains, which poses challenges to all project partners in terms of a common terminology, and project management methods, but enables development of inter-domain synergies like using the same sensor and actuator hardware for a broad range of services and use cases.

A Conformance Test Suite for Arden Syntax Compilers and Interpreters

The Arden Syntax for Medical Logic Modules is a standardized and well-established programming language to represent medical knowledge. To test the compliance level of existing compilers and interpreters no public test suite exists. This paper presents the research to transform the specification into a set of unit tests, represented in JUnit. It further reports on the utilization of the test suite testing four different Arden Syntax processors. The presented and compared results reveal the status conformance of the tested processors. How test driven development of Arden Syntax processors can help increasing the compliance with the standard is described with two examples. In the end some considerations how an open source test suite can improve the development and distribution of the Arden Syntax are presented.

Multimodal activity monitoring for home rehabilitation of geriatric fracture patients--feasibility and acceptance of sensor systems in the GAL-NATARS study

BACKGROUND

Demographic change will lead to a diminishing care workforce faced with rising numbers of older persons in need of care, suggesting meaningful use of health-enabling technologies, and home monitoring in particular, to contribute to supporting both the carers and the persons in need.

OBJECTIVES

We present and discuss the GAL-NATARS study design along with first results regarding technical feasibility of long-term home monitoring and acceptance of different sensor modalities.

METHODS

Fourteen geriatric participants with mobility-impairing fractures were recruited in three geriatric clinics. Following inpatient geriatric rehabilitation, their homes were equipped with ambient sensor components for three months. Additionally, a wearable accelerometer was employed. Technical feasibility was assessed by system and component downtimes, technology acceptance by face-to-face interviews.

RESULTS

The overall system downtime was 6%, effected by two single events, but not by software failures. Technology acceptance was rated very high by all participants at the end of the monitoring periods, and no interference with their social lives was reported.

DISCUSSION AND CONCLUSIONS

Home-monitoring technologies were well-accepted by our participants. The information content of the data still needs to be evaluated with regard to clinical outcome parameters as well as the effect on the quality of life before recommending large-scale implementations.

Information and communication technologies for promoting and sustaining quality of life, health and self-sufficiency in ageing societies--outcomes of the Lower Saxony Research Network Design of Environments for Ageing (GAL)

Many societies across the world are confronted with demographic changes, usually related to increased life expectancy and, often, relatively low birth rates. Information and communication technologies (ICT) may contribute to adequately support senior citizens in aging societies with respect to quality of life and quality and efficiency of health care processes. For investigating and for providing answers on whether new information and communication technologies can contribute to keeping, or even improving quality of life, health and self-sufficiency in ageing societies through new ways of living and new forms of care, the Lower Saxony Research Network Design of Environments for Ageing (GAL) had been established as a five years research project, running from 2008 to 2013. Ambient-assisted living (AAL) technologies in personal and home environments were especially important. In this article we report on the GAL project, and present some of its major outcomes after five years of research. We report on major challenges and lessons learned in running and organizing such a large, inter- and multidisciplinary project and discuss GAL in the context of related research projects. With respect to research outcomes, we have, for example, learned new knowledge about multimodal and speech-based human-machine-interaction mechanisms for persons with functional restrictions, and identified new methods and developed new algorithms for identifying activities of daily life and detecting acute events, particularly falls. A total of 79 apartments of senior citizens had been equipped with specific "GAL technology", providing new insights into the use of sensor data for smart homes. Major challenges we had to face were to deal constructively with GAL's highly inter- and multidisciplinary aspects, with respect to research into GAL's application scenarios, shifting from theory and lab experimentation to field tests, and the complexity of organizing and, in our view, successfully managing such a large project. Overall it can be stated that, from our point of view, the GAL research network has been run successfully and has achieved its major research objectives. Since we now know much more on how and where to use AAL technologies for new environments of living and new forms of care, a future focus for research can now be outlined for systematically planned studies, scientifically exploring the benefits of AAL technologies for senior citizens, in particular with respect to quality of life and the quality and efficiency of health care.

An HL7-FHIR-based Object Model for a Home-Centered Data Warehouse for Ambient Assisted Living Environments

Current AAL environments focus on assisting a single person with seperated technologies. There is no interoperability between sub-domains in home environments, like building energy management or housing industry services. BASIS (Building Automation by a Scalable and Intelligent System) aims to integrate all sensors and actuators into a single, efficient home bus. First step is to create a semtically enriched data warehouse object model. We choose FHIR and built an object model mainly based on the Observation, Device and Location resources with minor extensions needed by AAL-foreign sub domains. FHIR turned out to be very flexible and complete for other home related sub-domains. The object model is implemented in a separated software-partition storing all structural and procedural data of BASIS.

Rolling Medical Practice: Ambulant Mobile Medical Care for Rural Areas

We designed, constructed, and evaluated a mobile medical care vehicle called "Rollende Arztpraxis" (rolling medical practice, RMP) that delivers the full medical care of a general practitioner to increase medical care supply in rural areas. Six communities have been identified, where the RMP has been visited 501 times in 14 months. Two different schedules of stops and treatment times have been tested. We show that the RMP treated mainly elderly and multimorbid patients. An accompanying study showed high acceptance and satisfaction of treated patients and treating doctors. An economic evaluation of three different utilization models with three treatment modes each showed no financial sustainability. We show that ambulatory care in rural areas can be complemented by a mobile care unit, if legal and financial barriers can be overcome.

A methodological framework for the analysis of highly intensive, multimodal and heterogeneous data in the context of health-enabling technologies and ambient-assisted living

BACKGROUND

When applying health-enabling technologies (HET), researchers are faced with analyzing highly intensive, multimodal and heterogeneous data sets. Experience has shown that there is a lack of understanding concerning the relationship of analysis methods suitable for such data sets and their appropriate application.

OBJECTIVES

The objective of this paper is to describe the present situation when analyzing data of HET and the main problems in this context, to present a nomenclature suitable for analysis methods in the context of HET, to present an example dealing with geriatric diseases that highlights the problems and the urgent need for results and to explain some steps for future work.

METHODS

Nomenclatures as standard tools in information processing are applied.

RESULTS

We present an open three-axial mono-hierarchical nomenclature called SNOCAP-HET. Moreover, we explain other ideas to overcome the lack of systematization within the set of analysis methods suitable for HET.

CONCLUSIONS

Our approach allows for an extension of SNOCAP-HET and will allow for the development and evaluation of different measures for the appropriateness of analysis methods given a certain highly intensive, multimodal and heterogeneous data set in the context of HET. Our final future aim is to obtain better results when analyzing medical data.

Rollende arztpraxis - first results of an ambulant mobile care model for rural areas

German medical care is going to suffer from a decreasing number of general practitioners due to demographic change. We study if ambulatory care in rural areas can be complementary ensured by a mobile care unit. A medical care van - the "rolling medical practice" (RMP) - has been constructed based on care scenarios created for rural communities in northern Germany. Performance and acceptance of the RMP is evaluated by constant monitoring of anonymized medical documentation and questionnaires. The RMP is visiting six villages on two days a week in a three-week interval. It is constructed from a standard van with a custom box body fully equipped for general care needs. Actually treated care cases meet expectations and are acute as well as chronicle symptoms. Case numbers range from 6 to 50 visits in 5 month. We showed that almost full ranged mobile medical care, as supplement to general medical supply is possible.

Development and clinical validation of an unobtrusive ambulatory knee function monitoring system with inertial 9DoF sensors

Patients suffering from end-stage knee osteoarthritis are often treated with total knee arthroplasty, improving their functional mobility. A number of patients, however, report continued difficulty with stair ascent and descent or sportive activity after surgery and are not completely satisfied with the outcome. State-of-the-art analyses to evaluate the outcome and mobility after knee replacement are conducted under supervised settings in specialized gait labs and thus can only reflect a short period of time. A number of external factors may lead to artificial gait patterns in patients. Moreover, clinically relevant situations are difficult to simulate in a stationary gait lab. In contrast to this, inertial sensors may be used additionally for unobtrusive gait monitoring. However, recent notable approaches found in literature concerning knee function analysis have so far not been applied in a clinical context and have therefore not yet been validated in a clinical setting. The aim of this paper is to present a system for unsupervised long-term monitoring of human gait with a focus on knee joint function, which is applicable in patients' everyday lives and to report on the validation of this system gathered during walking with reference to state-of-the-art gait lab data using a vision system (VICON Motion System). The system KINEMATICWEAR - developed in close collaboration of computer scientists and physicians performing knee arthroplasty - consists of two sensor nodes with combined tri-axial accelerometer, gyroscope and magnetometer to be worn under normal trousers. Reliability of the system is shown in the results. An overall correlation of 0.99 (with an overall RMSE of 2.72) compared to the state-of-the-art reference system indicates a sound quality and a high degree of correspondence. KINEMATICWEAR enables ambulatory, unconstrained measurements of knee function outside a supervised lab inspection.

Performance comparison of accelerometer calibration algorithms based on 3D-ellipsoid fitting methods

Calibration of accelerometers can be reduced to 3D-ellipsoid fitting problems. Changing extrinsic factors like temperature, pressure or humidity, as well as intrinsic factors like the battery status, demand to calibrate the measurements permanently. Thus, there is a need for fast calibration algorithms, e.g. for online analyses. The primary aim of this paper is to propose a non-iterative calibration algorithm for accelerometers with the focus on minimal execution time and low memory consumption. The secondary aim is to benchmark existing calibration algorithms based on 3D-ellipsoid fitting methods. We compared the algorithms regarding the calibration quality and the execution time as well as the number of quasi-static measurements needed for a stable calibration. As evaluation criterion for the calibration, both the norm of calibrated real-life measurements during inactivity and simulation data was used. The algorithms showed a high calibration quality, but the execution time differed significantly. The calibration method proposed in this paper showed the shortest execution time and a very good performance regarding the number of measurements needed to produce stable results. Furthermore, this algorithm was successfully implemented on a sensor node and calibrates the measured data on-the-fly while continuously storing the measured data to a microSD-card.

Assessment of risk factors for post-rewarming "rebound hyperthermia" in cardiac arrest patients undergoing therapeutic hypothermia

INTRODUCTION

The outcomes associated with therapeutic hypothermia (TH) after cardiac arrest, while overwhelmingly positive, may be associated with adverse events. The incidence of post-rewarming rebound hyperthermia (RH) has been relatively unstudied and may worsen survival and neurologic outcome. The purpose of this study was to determine the incidence and risk factors associated with RH as well as its relationship to mortality, neurologic morbidity, and hospital length of stay (LOS).

METHODS

A retrospective, observational study was performed of adult patients who underwent therapeutic hypothermia after an out-of-hospital cardiac arrest. Data describing 17 potential risk factors for RH were collected. The primary outcome was the incidence of RH while the secondary outcomes were mortality, discharge neurologic status, and LOS.

RESULTS

141 patients were included. All 17 risk factors for RH were analyzed and no potential risk factors were found to be significant at a univariate level. 40.4% of patients without RH experienced any cause of death during the initial hospitalization compared to 64.3% patients who experienced RH (OR: 2.66; 95% CI: 1.26-5.61; p=0.011). The presence of RH is not associated with an increase in LOS (10.67 days vs. 9.45 days; absolute risk increase=-1.21 days, 95% CI: -1.84 to 4.27; p=0.434). RH is associated with increased neurologic morbidity (p=0.011).

CONCLUSIONS

While no potential risk factors for RH were identified, RH is a marker for increased mortality and worsened neurologic morbidity in cardiac arrest patients who have underwent TH.

High intensity, multimodality and incoherence: grand challenges in the analysis of data for health-enabling technologies

When working with health-enabling technologies, researchers all over the world usually have to analyze highly intensive, multimodal and incoherent data. We explain that there is a lack of systematization within the set of methods of analysis suitable for these data. As a first step towards a methodology in this context, we present the Systematic Nomenclature for Contexts, Analysis Methods and Problems in Health-Enabling Technologies (SNOCAP-HET).

Some thoughts on personal living environments as new diagnostic and therapeutic areas

Some thoughts on personal living environments as new diagnostic and therapeutic areas are presented, considering the following aspects: current potentials for diagnosis and therapy in personal living environments, consequences for care processes and for health information systems architectures and infrastructures, and informational self-determination and privacy. They may stimulate further discussion on respective research.

Design and implementation of the standards-based personal intelligent self-management system (PICS)

Against the background of demographic change and a diminishing care workforce there is a growing need for personalized decision support. The aim of this paper is to describe the design and implementation of the standards-based personal intelligent care systems (PICS). PICS makes consistent use of internationally accepted standards such as the Health Level 7 (HL7) Arden syntax for the representation of the decision logic, HL7 Clinical Document Architecture for information representation and is based on a open-source service-oriented architecture framework and a business process management system. Its functionality is exemplified for the application scenario of a patient suffering from congestive heart failure. Several vital signs sensors provide data for the decision support system, and a number of flexible communication channels are available for interaction with patient or caregiver. PICS is a standards-based, open and flexible system enabling personalized decision support. Further development will include the implementation of components on small computers and sensor nodes.

Wearable sensors in healthcare and sensor-enhanced health information systems: all our tomorrows?

Wearable sensor systems which allow for remote or self-monitoring of health-related parameters are regarded as one means to alleviate the consequences of demographic change. This paper aims to summarize current research in wearable sensors as well as in sensor-enhanced health information systems. Wearable sensor technologies are already advanced in terms of their technical capabilities and are frequently used for cardio-vascular monitoring. Epidemiologic predictions suggest that neuropsychiatric diseases will have a growing impact on our health systems and thus should be addressed more intensively. Two current project examples demonstrate the benefit of wearable sensor technologies: long-term, objective measurement under daily-life, unsupervised conditions. Finally, up-to-date approaches for the implementation of sensor-enhanced health information systems are outlined. Wearable sensors are an integral part of future pervasive, ubiquitous and person-centered health care delivery. Future challenges include their integration into sensor-enhanced health information systems and sound evaluation studies involving measures of workload reduction and costs.

Health-enabling technologies for the elderly--an overview of services based on a literature review

BACKGROUND

Services for the elderly based on health-enabling technologies promise to contribute significantly to the efficiency and effectiveness of future health care. Due to this promise, over the last years the scientific community has designed a complex variety of these valuable innovations. A systematic overview of the developed services would help to better understand their opportunities and limitations.

OBJECTIVE

To obtain a systematic overview of services for the elderly based on health-enabling technologies and to identify archetypical service categories.

METHODS

We conducted a literature review using PubMed and retrieved 1447 publications. We stepwise reduced this list to 27 key publications that describe typical service archetypes.

RESULTS

We present six archetypical service categories, namely handling adverse conditions, assessing state of health, consultation and education, motivation and feedback, service ordering and social inclusion and describe their implementation in current research projects.

ARDEN2BYTECODE: a one-pass Arden Syntax compiler for service-oriented decision support systems based on the OSGi platform

Patient empowerment might be one key to reduce the pressure on health care systems challenged by the expected demographic changes. Knowledge based systems can, in combination with automated sensor measurements, improve the patients' ability to review their state of health and make informed decisions. The Arden Syntax as a standardized language to represent medical knowledge can be used to express the corresponding decision rules. In this paper we introduce ARDEN2BYTECODE, a newly developed open source compiler for the Arden Syntax. ARDEN2BYTECODE runs on Java Virtual Machines (JVM) and translates Arden Syntax directly to Java Bytecode (JBC) executable on JVMs. ARDEN2BYTECODE easily integrates into service oriented architectures, like the Open Services Gateway Initiative (OSGi) platform. Apart from an evaluation of compilation performance and execution times, ARDEN2BYTECODE was integrated into an existing knowledge supported exercise training system and recorded training sessions have been used to check the implementation.

A method to align the coordinate system of accelerometers to the axes of a human body: The depitch algorithm

One of the key problems in accelerometry based gait analyses is that it may not be possible to attach an accelerometer to the lower trunk so that its axes are perfectly aligned to the axes of the subject. In this paper we will present an algorithm that was designed to virtually align the axes of the accelerometer to the axes of the subject during walking sections. This algorithm is based on a physically reasonable approach and built for measurements in unsupervised settings, where the test persons are applying the sensors by themselves. For evaluation purposes we conducted a study with 6 healthy subjects and measured their gait with a manually aligned and a skewed accelerometer attached to the subject's lower trunk. After applying the algorithm the intra-axis correlation of both sensors was on average 0.89±0.1 with a mean absolute error of 0.05g. We concluded that the algorithm was able to adjust the skewed sensor node virtually to the coordinate system of the subject.

Mining geriatric assessment data for in-patient fall prediction models and high-risk subgroups

Background

Hospital in-patient falls constitute a prominent problem in terms of costs and consequences. Geriatric institutions are most often affected, and common screening tools cannot predict in-patient falls consistently. Our objectives are to derive comprehensible fall risk classification models from a large data set of geriatric in-patients' assessment data and to evaluate their predictive performance (aim#1), and to identify high-risk subgroups from the data (aim#2).

Methods

A data set of n = 5,176 single in-patient episodes covering 1.5 years of admissions to a geriatric hospital were extracted from the hospital's data base and matched with fall incident reports (n = 493). A classification tree model was induced using the C4.5 algorithm as well as a logistic regression model, and their predictive performance was evaluated. Furthermore, high-risk subgroups were identified from extracted classification rules with a support of more than 100 instances.

Results

The classification tree model showed an overall classification accuracy of 66%, with a sensitivity of 55.4%, a specificity of 67.1%, positive and negative predictive values of 15% resp. 93.5%. Five high-risk groups were identified, defined by high age, low Barthel index, cognitive impairment, multi-medication and co-morbidity.

Conclusions

Our results show that a little more than half of the fallers may be identified correctly by our model, but the positive predictive value is too low to be applicable. Non-fallers, on the other hand, may be sorted out with the model quite well. The high-risk subgroups and the risk factors identified (age, low ADL score, cognitive impairment, institutionalization, polypharmacy and co-morbidity) reflect domain knowledge and may be used to screen certain subgroups of patients with a high risk of falling. Classification models derived from a large data set using data mining methods can compete with current dedicated fall risk screening tools, yet lack diagnostic precision. High-risk subgroups may be identified automatically from existing geriatric assessment data, especially when combined with domain knowledge in a hybrid classification model. Further work is necessary to validate our approach in a controlled prospective setting.

A literature overview and comparison of driving impairing condition assessment approaches by health enabling technologies

Due to demographic change, more elderly people have the need to preserve and support mobility by car despite age-related functional limitations. Since accidents by the elderly are primarily caused by age related limitations, and not by careless or irresponsible behavior, it may be beneficial to detect driving impairing conditions. The presented review gives an overview of technologies to detect driving impairing conditions like drowsiness and stress or excessive demand. A comparison of the approaches to detect these conditions suggests that a combination of approaches is the most feasible method. However, there are still few systems that focus on the elderly.

Sensors vs. experts - a performance comparison of sensor-based fall risk assessment vs. conventional assessment in a sample of geriatric patients

Background

Fall events contribute significantly to mortality, morbidity and costs in our ageing population. In order to identify persons at risk and to target preventive measures, many scores and assessment tools have been developed. These often require expertise and are costly to implement. Recent research investigates the use of wearable inertial sensors to provide objective data on motion features which can be used to assess individual fall risk automatically. So far it is unknown how well this new method performs in comparison with conventional fall risk assessment tools. The aim of our research is to compare the predictive performance of our new sensor-based method with conventional and established methods, based on prospective data.

Methods

In a first study phase, 119 inpatients of a geriatric clinic took part in motion measurements using a wireless triaxial accelerometer during a Timed Up&Go (TUG) test and a 20 m walk. Furthermore, the St. Thomas Risk Assessment Tool in Falling Elderly Inpatients (STRATIFY) was performed, and the multidisciplinary geriatric care team estimated the patients' fall risk. In a second follow-up phase of the study, 46 of the participants were interviewed after one year, including a fall and activity assessment. The predictive performances of the TUG, the STRATIFY and team scores are compared. Furthermore, two automatically induced logistic regression models based on conventional clinical and assessment data (CONV) as well as sensor data (SENSOR) are matched.

Results

Among the risk assessment scores, the geriatric team score (sensitivity 56%, specificity 80%) outperforms STRATIFY and TUG. The induced logistic regression models CONV and SENSOR achieve similar performance values (sensitivity 68%/58%, specificity 74%/78%, AUC 0.74/0.72, +LR 2.64/2.61). Both models are able to identify more persons at risk than the simple scores.

Conclusions

Sensor-based objective measurements of motion parameters in geriatric patients can be used to assess individual fall risk, and our prediction model's performance matches that of a model based on conventional clinical and assessment data. Sensor-based measurements using a small wearable device may contribute significant information to conventional methods and are feasible in an unsupervised setting. More prospective research is needed to assess the cost-benefit relation of our approach.

Monitoring systems for the support of home care

In this article, the design of a system for the ambient, unobtrusive and automatic monitoring of Activities of Daily Living (ADL) is described. In the context of the growing imbalance between (potentially young) caregivers and (most often older) people receiving care, technical monitoring systems may help to organise care more efficiently and to identify degrading abilities very early to trigger preventive measures. To improve the acceptance of the system described in this article, the selection process of the sensors to be integrated into the flat or to be worn by the older people has been steered by the results of focus group interviews with older people, their relatives and professional caregivers. The interviews revealed that these people would in general accept such systems, but security, mobility and communication aspects have to be clearly and appropriately addressed. In an experimental study the recognition rate of the activity 'preparation and intake of food or beverages' has been measured with two age groups (6 subjects, age between 25 and 40/mean 30 years and 5 subjects, age between 72 and 84/mean 75.3 years). The food preparation was detected with a sensitivity of 74.7% and a specificity of 84.2% using a vision sensor.