From on-body sensors to in-body data for health monitoring and medical robotics: A survey

Hernández, Sandra C.; Raison, Maxime; Alexandre, Torres; Gaudet, Guillaume; Achiche, Sofiane

doi:10.1109/giis.2014.6934279

Cited by 6 publications

(4 citation statements)

References 23 publications

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“…Indeed, on-body sensors (e.g., inertial measurement units, force sensors, electromyography, etc.) allow the recording of useful in-body data, such as internal efforts, range of motion, and muscle forces, to enable the design of exoskeletons [86].…”

Section: Challenges For Pediatric Accessmentioning

confidence: 99%

Current Trends and Challenges in Pediatric Access to Sensorless and Sensor-Based Upper Limb Exoskeletons

Gaudet

Raison

Achiche

2021

Sensors

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Sensorless and sensor-based upper limb exoskeletons that enhance or support daily motor function are limited for children. This review presents the different needs in pediatrics and the latest trends when developing an upper limb exoskeleton and discusses future prospects to improve accessibility. First, the principal diagnoses in pediatrics and their respective challenge are presented. A total of 14 upper limb exoskeletons aimed for pediatric use were identified in the literature. The exoskeletons were then classified as sensorless or sensor-based, and categorized with respect to the application domain, the motorization solution, the targeted population(s), and the supported movement(s). The relative absence of upper limb exoskeleton in pediatrics is mainly due to the additional complexity required in order to adapt to children’s growth and answer their specific needs and usage. This review highlights that research should focus on sensor-based exoskeletons, which would benefit the majority of children by allowing easier adjustment to the children’s needs. Sensor-based exoskeletons are often the best solution for children to improve their participation in activities of daily living and limit cognitive, social, and motor impairments during their development.

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Section: Challenges For Pediatric Accessmentioning

confidence: 99%

Current Trends and Challenges in Pediatric Access to Sensorless and Sensor-Based Upper Limb Exoskeletons

Gaudet

Raison

Achiche

2021

Sensors

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“…Apart from placing the sensors on the environment, on-body sensors [119] can provide both the contextual and physiological characteristics of agents that may be important in understanding ambient behaviours of the simulated agents. To get the best out of the sensor agents, sensors should not only be measuring devices but must also be cognitive [120].…”

Section: Dynamic Data-driven Multi-agent Systems (Dddmas)mentioning

confidence: 99%

Sensor-Driven, Spatially Explicit Agent-Based Models

Oloo¹

2019

Swarm Intelligence - Recent Advances, New Perspectives and Applications

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Conventionally, agent-based models (ABMs) are specified from well-established theory about the systems under investigation. For such models, data is only introduced to ensure the validity of the specified models. In cases where the underlying mechanisms of the system of interest are unknown, rich datasets about the system can reveal patterns and processes of the systems. Sensors have become ubiquitous allowing researchers to capture precise characteristics of entities in both time and space. The combination of data from in situ sensors to geospatial outputs provides a rich resource for characterising geospatial environments and entities on earth. More importantly, the sensor data can capture behaviours and interactions of entities allowing us to visualise emerging patterns from the interactions. However, there is a paucity of standardised methods for the integration of dynamic sensor data streams into ABMs. Further, only few models have attempted to incorporate spatial and temporal data dynamically from sensors for model specification, calibration and validation. This chapter documents the state of the art of methods for bridging the gap between sensor data observations and specification of accurate spatially explicit agent-based models. In addition, this work proposes a conceptual framework for dynamic validation of sensor-driven spatial ABMs to address the risk of model overfitting.

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“…Measurements of muscle forces, joint torques, muscle co-activation, etc., are examples of in-body data. These data are essential for understanding musculoskeletal illnesses, enhancing the effectiveness of clinical evaluations of them, carrying out duties related to health monitoring, and enhancing therapeutic treatment [ 10 ].…”

Section: Introductionmentioning

confidence: 99%

Prospect of Internet of Medical Things: A Review on Security Requirements and Solutions

Sadhu

Yanambaka

Abdelgawad

et al. 2022

Sensors

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With the widespread and increasing use of Internet-of-Things (IoT) devices in all aspects of daily life, a hopeful future for people, data, and processes is emerging. Extensive spans allow for an integrated life cycle to be created from home to enterprise. The Internet of Medical things (IoMT) forms a flourishing surface that incorporates the sensitive information of human life being sent to doctors or hospitals. These open an enormous space for hackers to utilize flaws of the IoMT network to make a profit. This creates a demand for standardizing regulations and a secure system. Though many authorities are making standards, there are some lacking in the system which makes the product vulnerable. Although many established mechanisms are present for the IoT network, there are a number of obstacles preventing its general implementation in the IoMT network. One of the adoption challenges is the IoMT devices itself, because many IoMT networks consist of battery-powered devices with constrained processing capability. A general overview of the different security integrations with IoT applications has been presented in several papers. Therefore, this paper aims to provide an overview of the IoMT ecosystem, regulations, challenges of standards, security mechanisms using cryptographic solutions, physical unclonable functions (PUF)-based solutions, blockchain, and named data networking (NDN) as well, with pros and cons.

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From on-body sensors to in-body data for health monitoring and medical robotics: A survey

Cited by 6 publications

References 23 publications

Current Trends and Challenges in Pediatric Access to Sensorless and Sensor-Based Upper Limb Exoskeletons

Current Trends and Challenges in Pediatric Access to Sensorless and Sensor-Based Upper Limb Exoskeletons

Sensor-Driven, Spatially Explicit Agent-Based Models

Prospect of Internet of Medical Things: A Review on Security Requirements and Solutions

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