Patent Application
20180368780
This invention is related to a people monitoring and personal assistance system, in particular elderly and people with special or cognitive needs, which system includes a number of sensors to determine descriptive parameters of the environment where the person is, and a number of sensors to determine at least the person's position in such environment and possibly the person's physiological parameters, as well as movements of the person.
Currently, systems to monitor people in specific environments, mostly limited by structural boundaries, for instance apartments, or closed environments, walled gardens or similar, assume to determine a person's position within the aforementioned environment with respect to an environment's topographic map and possibly to determine the person's physiological parameters using sensors, which are indicative of the person's well being.
Such systems, although apt for the goals they address, are nonetheless inappropriate for a real and proper monitoring function for a person's conditions to the aim of assistive purposes, above all for what concerns determining both physical, neurological and cognitive health conditions, and are incapable at all of rapidly and early determining emergency conditions such as possible cognitive pathologies or a decline in the monitored people's motor capabilities, since they do not correlate, in an algorithmic and sytematic way, information coming from sensors neither with time nor with rules able to describe quantitatively states of well being and states of danger.
The goal of the present invention is to realize a new welfare paradigm with a system able to monitor people's activities, both with respect to their positions in the environment, and with their postures, and with respect to the temporal evolution of said postures, and with respect to temporal relations between the said activities, for each single person even if more than one is present in the environment.
An additional goal is to refine the system to allow for the monitoring of a possibly elderly person living alone in an apartment or in assisted-living facilities, who can suffer from mild cognitive, neurological or physical disabilities.
An additional goal is to achieve an easy-to-use and cheap system.
Yet an additional goal is to achieve the aforementioned system adopting a modular architecture, whose components may be constituted by commercially available, components off-the-self hardware.
Additional goals are related to the achievement of a system characterized by:
The present invention achieves the aforementioned goals with a system of the kind described at the beginning, in which are envisioned:
According to an executive form, the signals of said sensors are represented by logical symbols with boolean values (true/false), and possibly with multiple truth values (e.g., fuzzy) and/or probabilistic.
Yet another executive form uses a data structure which is based on the formalism called Descriptive Logics or a formalism of equivalent expressive power.
In another executive form, symbols can be grouped and put into relation each other, and the related temporal information can be put into relation with them.
Classification can be performed using standard reasoning mechanisms, typical of Descriptive Logics, as well as by reasoning mechanisms with similar inferential power, like the so-called “instance checking” and the so-called “subsumption”, as well as by the methods with equivalent capabilities in other aforementioned representation systems.
In an executive form the dialogue can be formalized using formal grammars methods, and dialogue models represented in the taxonomic data structure, and even using speech comprehension and generation systems commercially available; the outcomes of the dialogue process are themselves represented by logical symbols over time, as boolean values (true/false), possibly with multiple truth values (e.g., fuzzy) and/or probabilistic, being such outcomes used by the classification process.
According to a further characteristic, determining dangerous states of the assisted person, as well as uncommon events, can be achieved by comparing symbols in the assertional structure with predefined symbols defined in the terminological structure.
An executive form implements alarms using suitable commercial systems.
An executive form uses an algorithm that performs an evaluation of symbols representing signals related to position and posture of the assisted person and their relevant variations over time, as well as symbols representing physiological parameters and their relevant variations over time; the mentioned algorithm classifies such symbols following predefined schemes stored in the terminological part of the data structure; the aforementioned symbols can be put into relation formally with motor and/or postural activities and/or physiological parameters behaviours, represented in the terminological structure, as well as models and/or descriptions of actions of the assisted person, composed either sequentially and concurrently, by simpler actions over time.
A further executive form includes an algorithm able to compare the schemes stored in the terminological part of the data structure with the symbols corresponding to data acquired by sensors by using also parameters chosen at least among the following: position of the monitored person and/or his/her posture and/or his/her physiological parameters and/or the velocity of variation of the aforementioned three ones, and/or the temporal duration of such variations and/or the absence of such variations and/or the congruity of postures with actual positions in the environment with respect to the same parameters related to the models stored in the terminological part of the data structure which describe the actual motion activities or postural states.
An executive form includes an algorithm able to compare schemes stored in the terminological part of the data structure, associated to physiological parameters, with the symbols to data acquired by sensors by using also parameters chosen at least among the following: body temperature of the monitored person and/or his/her blood pressure and/or his/her heart rate and/or the velocity of variation of the aforementioned three ones, and/or the temporal duration of such variations and/or the absence of such variations a with respect to the same parameters related to the models stored in the terminological part of the data structure.
The predefined behavioural model, stored in the terminological part of the data structure, can be personalized using a training phase in which information about the peculiar behavioural features of the monitored person are collected, which correspond to common behavioural conditions.
Such training or personalization can take place at the installation or set up phase, by a simple textual and/or graphical interface, or/and by implementing the classification program as an algorithm, for instance a neural network or any other algorithm with comparable expressive and computational capabilities, able to execute learning steps during its execution since the set up phase.
According to another improvement, the system envisions that data related to position and movement of the monitored person in the environment and/or of posture and its variation can be integrated with data related to the monitored person's physiological parameters, acquired by sensors, possibly commercially available, such as temperature, blood pressure, heart rate and/or cardiac traces and other physiological parameters.
Another executive form of the system can foresee that data related to environmental conditions, such as temperature, humidity, luminosity level, atmospheric pressure, presence of smoke and/or or dangerous and/or harmful gases and similar, occurrence of noises and source type or effect of noise production, be combined as well.
Thanks to symbols corresponding to these additional data, the algorithm can be defined as a control procedure that refines the classification of the detected activities on the basis of data related to the position in the environment and/or its variation and/or to data related to the posture and/or its variation with the monitored person's physiological parameter data and/or also data related to environmental conditions, therefore improving the accuracy of the analysis and the classification of symbols describing the state of the monitored person.
When the classification of symbols and/or of combinations of symbols and/or of temporal sequences of symbols indicates a condition of anomalous behaviour of the monitored person, or a behaviour outside the usual behavioural schemes and/or a dangerous situation, it is possible to automatically generate alarms to send to a series of persons and/or organisations selected during the configuration or installation phase (e.g. relatives, medical or trained or emergency personnel, firemen, neighbours, and so on) who is specifically trained to intervene to deal with the conditions detected by the classification procedure itself.
It is also possible to foresee in the system either passive communication means to interact with the monitored person, for example with the emission of messages using devices distributed in the environment, such as a series of monitor, a radio, a TV set, or a speaker system, or similar digital devices.
If the classification procedure detects an anomalous behavioural condition of the monitored person, or outside the common behavioural schemes, and/or a dangerous situation, possibly related to physiological conditions then the system allows for intervening in an automated and quick way, with the best possible use of available interaction technologies and devices.
Furthermore, by periodically classifying symbols and/or combinations of symbols and/or the related temporal sequences corresponding to the assisted person's activities, it is also possible to measure the evolution of the same person's cognitive capabilities and/or physiological conditions, therefore being able to pro-actively intervene not only to safeguard the said person from a sudden dangerous condition in a short time period, but also to set the necessary therapeutic ground to deal with worsening conditions, when the pathology is still in its onset.
In the present invention the term “dialogue” is defined as an interaction between the system and the assisted person, possibly repeated several times, in which the system sends vocal messages to the said person waiting for a response by the person.
Several kinds of responses are possible, that can be executed in alternative or in combination, consisting either in a vocal response or in the execution of a movement detected by a sensor (like a gesture or moving to a different place).
In an executive form, the interpretation of the response can give an information represented by the system as a symbol, which, like other symbols, is put into relations to other symbols, including temporal representations, and suitably classified.
Following a further characteristic, the datum coming from a dialogue reply can be used to generate a symbol that describes a variation with respect to other symbols; such symbol can, after its classification, make the algorithm generate further and iterative messages waiting for a response by the monitored person.
The dialogue iterative phase consists of the abovementioned steps; in more details, they consist of a sequence of messages sent by the system and series of responses by the monitored person until:
Following a further characteristic, an alarm is generated in any case the number of iteration in the dialogue phase has exceeded a given safety value without concluding that the monitored person's state is safe, so that the algorithm has characteristics of intrinsic safety with respect to the monitored person.
An example of the system's execution according to the present invention foresees a four-layer modular and scalable architecture, such as:
i. a level is constituted by the hardware infrastructure;
ii. a level is constituted by the algorithm coded in the software executed as series of operative instructions by the aforementioned hardware infrastructure implementing the classification procedure based on the taxonomic structure and the dialogue;
iii. a level with a database of symbols representing models and/or schemes of behaviours, of symbols describing some environment characteristics, of symbols referring to possible dialogues described in a logical formalism based on Description Logics, the present level including:
iv. a communication/data sharing level among the system's hardware devices and with external systems with respect to the considered system, such as external communication networks, computers, smartphones and other digital devices.
The hardware is advantageously constituted by a series of modular devices, at least one part of which is wearable, to distribute in the environment. The hardware devices communicate with each other using different possibly wireless modalities and can in part be developed ad hoc, and partially are constructed in a personalized way, while partially can be interfaced with commercially available devices or use such devices.
The choice of the type and number of the hardware devices adheres to the principle of cost minimization, identifying the minimum set of such devices able to meet the goal performance with respect to the contingent situation related to the system use, complying the before mentioned principle of intrinsic safety, but allowing at the same time for expansions and adjustments as well as a effective energetic autonomy; the adopted technologies are the most up-to-date provided they are reliable and with a meaningful utilization horizon.
According to the present invention, the system therefore implements an algorithm which, using also procedures for classification on data structures based on Description Logics or logical formalisms of comparable or higher expressive capacity, in order to classify symbols and/or temporal sequences of symbols in the assertional part of the data structure, is able to determine if such symbols and/or combinations of symbols and/or temporal sequences of symbols correspond to models described in the terminological part of the data structure, and decides whether to activate a dialogue procedure with the assisted person to acquire further symbols and/or combinations of symbols and/or temporal sequences of symbols, so definitely being able to activate or not alarm procedures, for example to alert medical personnel or not cohabiting relatives, neighbours, firemen etc. according to the alarm's type and severity. In particular the algorithm can analyze symbols and/or combinations of symbols and/or temporal sequences of symbols corresponding to the acquired data from sensors and represented in the assertional part of the data structure, hence classifying them as either compatible or not compatible with normed behaviours in every day life, and/or with habits specific to the assisted person.
Therefore, the system defined in the present invention is able to understand the assisted person's wellness level on the basis of his/her habits and personalized parameters, to foresee anomalous and potentially dangerous situations, to promptly intervene in case of danger, to dialogue with the person to increase its understanding of what is happening, to store meaningful data for a further successive assistance, to understand gestures, motion, same person's position, to learn calibrated modifications of common habits, to manage help requests to the outside, to assure a personalized adaptation also by not trained personnel, such as the monitored person's relatives or other.
With respect to the taxonomic data structure, formalisms like Description Logic can be used, or equivalent ones from the point of view of the formal expressivity and of the computational capabilities.
The taxonomic database can be filled with suitably symbols and/or combinations of symbols and/or temporal sequences of symbols implementing models of different types, hence adapted and/or personalized during the setup phase in order to include specific characteristics, habits, customs and practices of the assisted person (activities schedule, gestures, ranges of measured quantities and so on, as described in the following).
Furthermore, the system itself, during monitoring, can update symbols and/or combinations of symbols and/or temporal sequences of symbols in the assertional part of the taxonomic data structure, on the base of observations, under supervision of responsible persons or trained personnel. The symbols and/or combinations of symbols and/or temporal sequences of symbols and in particular their truth vales in this way updated referred to actions and their modifications in time can also be made available to healthcare personnel to control the evolution of diseases and/or impairments and/or of the simple aging of the assisted person.
With respect to the communication among devices, this takes place preferably using the original protocols, such as those based on IEEE 802, Bluetooth, UWB 868 MHz, Radio-Frequency IDentification (RFID, ISO/IEC 18000), and further modifications and evolutions, which interface all, or partially, the devices and, given their feature of being open to any user, are able to guarantee security, expandability, and connection to external systems, such as for example, a smartphone or other digital devices.
This and other features and advantages of this invention result more clearly from the following description of a few examples illustrated in the attached Figures, where:
The environment illustrated in
Therefore, features described with respect to a domestic environment, but which can be foreseen also in the conditions of the aforementioned outdoor environment, are intended to be described by analogy also in outdoor, not limited and/or not delimited environments.
With respect to
Furthermore, typically a domestic environment includes a water supply system, a power supply system, possibly also a methane supply system, a heating system and/or a system to generate and distribute hot water, as well as the related measurement and control units.
A person living in the domestic environment is referred to as P.
The system according to the present invention foresees that the domestic environment be provided with different sensors able to acquire data related to one or more environmental parameters, which are indicated respectively with the “triangle” graphic sign and identified with the symbol that denotes the room where the sensors are located, and a number. In particular, the sensors to be located in the kitchen are indicated as a whole as K1, those in the bathroom as B1, those in the entrance hall as I1, those in the bedroom as L1, those in the living room as S1 and those in the balcony as BA1.
An essential type of sensors and/or combination of sensors is constituted by sensors to detect the presence of the monitored person, of their position and the variation of their position over time, for what concerns both position itself, but also the speed of variation and/or accelerations and/or decelerations.
These measurements can be combined with a digital model or virtual topological map of the domestic environment, possibly comprising also the position of several doors, windows and/or similar and/or at least several furniture elements, as well as the bathroom and/or the kitchen, and represented in the data structure of taxonomic type by means of symbols and/or combinations of symbols.
With respect to
Thanks to this time-based position information and with reference to the virtual map of the environment, it is possible to localize, even precisely, the monitored person as well as to track his/her motion.
The indications of the sensors separated for each room do not have to be intended as limiting with respect to the fact that at least a number of sensor's types could be physically located only in one or a few rooms and could extend their sensing range also to rooms where they are not physically present.
Environmental sensors can be of any given type and, as an example, they can include one or more sensors of the following typologies: temperature sensors, acoustic sensors, light sensors, smoke or gas sensors, sensors to detect the presence of liquids on the floor, water flow sensors, power consumption sensors, sensors to detect opening and/or closing of doors and/or windows and/or French windows or similar.
According to an additional refinement of the system according to the present invention, it is possible to foresee environmental sensors able to determine the environment's topological conditions or at least part of them, and which allow for the automated generation of a digital map of the environment where the assisted person is present.
This is particularly important when operating in outdoor, non-delimited environments. In this case, it is possible, in order to achieve the automated generation of a digital map of the environment, to use also sensors already available in the area to map the environment, such as, for example, cameras for traffic monitoring, security cameras and/or other sensors. Just in case, this information can be combined with other information related to street maps and/or topographic or similar, which can downloaded to navigation systems such as those available in mobile phones or in smartphones.
The monitored person denoted as P wears one or more wearable and/or portable sensors symbolically represented by triangle P1 in
These sensors can be of any types and can include sensors of one or more physiological parameters, and also sensors to detect posture and/or its variations and/or sensors to detect motions executed by the monitored person. Also for such posture and/or movement variations, data are collected as a functions of time to determine the possible speed of execution related to posture variations and/or motions and possibly also to measure accelerations and/or decelerations.
In addition to wearable sensors, the monitored persons can stably carry with them a communication and/or computation device, i.e., able to execute programs and applications, such as smartphones, PDAs or similar digital devices.
As an additional improvement of the system according to the present invention, the communication device can be a Google Watch or an Apple Watch or a similar digital device, which acts as a kind of satellite device of a portable communication device such as, for example, a smartphone or a similar digital device.
For the sensors and the additional detection and personal communication devices described above, it is advantageous to use at the best of their characteristics already existing and largely commercially available devices.
In the case of these devices, it is important that they are provided with communication interfaces according to one or more existing communication protocols (or compatible with new standards not yet existing at the moment the present invention is described), and that they are suitable to be part of device networks, all of them communicating with each other.
The use of standard network protocols allows the system according to the present invention to be very easily scalable and modular and relatively low-cost, therefore allowing for progressively expanding the system itself as long as the assisted person's needs expand in their turn.
When monitoring an outdoor environment, the system according to the present invention foresees that a portable communication device, for instance a mobile phone and/or a smartphone and/or similar digital devices, play the role of access point for the assisted person's wearable devices towards the system's network.
In case of outdoor or non-delimited environments, this communication device keeps the link between the person and the system according to the present invention.
In case the system according to the present invention is implemented as an algorithm coded into a software under the form of instructions for a processor and memorized in a server and/or a remote server and/or distributed in a cloud server, and/or in a portable device of the monitored person, like a mobile phone, a smartphone or similar digital devices, being in this last case an application, for instance constituted by a software application executed on a smartphone or other portable communication device, then it is possible to distribute the functions of the system itself partially in the server and/or the remote server and/or the cloud server and partially in the portable device of the assisted person, such that to guarantee in any conditions a minimum level of connection and functionalities of the aforementioned system.
As indicated in
Data collected by sensors as to say the digital maps denoted 31, the environmental parameters denoted 32, data about positions and movements denoted 33, data about posture and its variations denoted 34, data about physiological conditions denoted 35 are stored in corresponding data structures of taxonomic type, as described in the previous. A clock denoted associates data with time stamps and duration measurements, therefore adding information able to associate to symbols and/or to combinations of symbols and/or to temporal sequences of symbols in the assertional part of the taxonomic data structure also information that allow interpreting data associating symbols themselves with a certain type of voluntary or accidental behaviour.
By synchronizing the timing of detection of the various data from the various sensors it is possible to correlate at least part of the symbols and/or to combinations of symbols and/or to temporal sequences of symbols in the assertional part of the taxonomic data structure in order to define more precisely the behaviour of the person being monitored.
Considering an example referring to the figures, the system according to the present invention correlates the location of the assisted person located in a particular room, such as the kitchen for example, and/or with a place inside that room, such as “near the stove”. At the same time, a given posture is detected as well as the execution of certain movements of the body of the said person. Moreover it is possible to detect measures of gas or electricity use (depending on the stove type).
The duration and the execution speed of some movements can be also monitored.
It is also possible to correlate the measurements with the data related to the monitored person's physiological parameters.
If the data are compatible with each other it can be considered at a first instance that the behaviour is appropriate and not unusual.
Furthermore, having access to models that encode behaviour patterns known as standard and healthy for the assisted person in terms of symbols and/or combinations of symbols and/or temporal sequences of symbols, that can be used to understand whether symbols and/or combinations of symbols and/or temporal sequences of symbols representing data coming from sensors in the assertional part of the data structure do correspond to dangerous situations and/or bad habits of the person, it is possible to put into relation the measured data with parameters of the standard models to classify what type of activity is carried out by the said person and if the same activity is carried out in the normal way.
A further example is the detection of the assisted person in the bedroom, possibly in a position corresponding to the bed and, at the same time, an absence of movement and/or a reduced number of movements and/or the physiological parameters compatible with a condition of rest. An ambient light sensor can also complete the picture by detecting low light intensity, or its absence, compatible with a condition of rest.
Advantageously, in addition to generating a set of models encoding standard behavioural models related to the healthy characteristics, habits, customs and practices of the assisted person by means of symbols and/or combinations of symbols and/or temporal sequences of symbols, common for the most part of people, or referring to standard behavioural models related to every day custom actions specific to the assisted person, the system, according to the present invention, can provide a classifier of symbols and/or combinations of symbols and/or temporal sequences of symbols corresponding to the data detected by the sensors, denoted 40 in the figure, being such models suitably coded, or the result of a learning process or personalization; this process can be carried out at in the installation and/or setup phase of the said system, and can take into account all feedbacks that operators of the said system give about performed activities of the assisted person.
The system according to the present invention can also provide a unit generating alerts and/or messages and/or alarms, denoted 50; such messages can be generated according to the type of behaviour or detected situation, and sent as requests for help to the outside, also operated by personnel not specialized, such as relatives, medical or paramedical personnel, personnel trained to deal with emergencies, firefighters, neighbours, etc. The messages to the monitored person, as to say, the aforementioned dialogue, can be either a message without no feedback expected from the recipient, or, preferably, with a feedback expected from her/him. The system according to the present invention dialogues with the assisted person using a limited form of natural language, using speech synthesis, to decide, using the aforementioned dialogue, whether the monitored person is in a dangerous situation, the danger gravity, or simply to remind the assisted person about some important information, for example suggesting or pushing the person to carry out some suitable activity, recreational activities or typical of everyday life.
The dialogue method is such that questions (by the system) and relative answers (by the monitored person), encoded by the system according to the present invention as symbols and/or combinations of symbols and/or temporal sequences of symbols, and classified by inferential algorithms typical of logical formalisms like Description Logic, can be put into relation with the behavioural models stored in the terminological components of the data structure, in order to understand the person's state and the possible danger situations, or simply of attention needed.
In particular, when it is necessary to communicate with the assisted person it is possible to foresee using adequate passive communication devices, possibly commercially available, for diffusing such messages e.g., through the home TV, or suitable fixed devices in the home, or ad hoc portable devices, or by means of the portable device for monitoring, or devices to which the same monitored person can respond and communicate or send also requests; those devices can be ad hoc communication equipment, even industry standard and interfaced to the system, or the portable monitoring device itself worn by the assisted person.
Dialogues with the assisted person can be either predefined and formally defined as symbols and/or combinations of symbols and/or temporal sequences of symbols, as well as rule-based models and/or models based on formal grammars, as well as designed in the set up or installation phase by a suitably expert supervising person.
With regard to the part of the taxonomic data structure representing behavioural models, in particular those models representing habits specific to the assisted person, this can be done by providing the system with a learning phase performed on a limited number of experimental users and for a limited period of time.
The data structure of taxonomic type, which comprises the normative models for the actions of the assisted person, the model of the environment in which the assisted person is monitored, normative models for the typical habits of the said person, the models possibly based on formalisms rules for the generation of messages and/or announcements and/or alarms, possibly models based on rule-based formalisms and/or possibly related to formal grammars, together with the components of the data acquisition system, translation of data originating from sensors in appropriate symbols and/or combinations of symbols and/or temporal sequences of symbols, the classification methods typical of the Description Logics formalisms, the components of the dialogue management system with the assisted person or of the alarm communication, are the minimal constituents of the algorithm which implements the system according to the present invention.
The system according to the present invention is able to understand the level of welfare of the assisted person according to his/her habits and even customized parameters, to predict critical situations, to intervene promptly in case of danger, to dialogue with the person to increase the understanding of what is happening, to accumulate significant data to support further following assistance, to understand gestures, movement, position of the said person, to learn calibrated changes of his/her habits, to handle the requests for help toward outside the home (relatives, trained personnel, public and/or private care institutions, police etc.), to support a personalized adaptation, even by non specialized people, such as relatives of the person being monitored, always complying with the aforementioned principle of intrinsic safety.
The taxonomic data structure can be tailored with respect to the assisted person in the set up phase, by a properly expert supervisor, or in a successive phase; this adaptation can be made easy with a suitably usable software interface, textual and/or graphical. The said interface, suitably designed, can allow even non trained persons to carry out tailoring the system according to the present invention.
In its basic form the system according to the present invention includes the following functional characteristics:
This implies the presence of devices to be placed in the monitored environment and a topological model of the said environment in which the assisted person acts.
As mentioned previously, the system according to the present invention can use sensors and/or transponders and/or similar digital devices to detect the presence of the said person in certain areas and can also include an automatic mapping system able to deduce the topology of the said environment. This can be achieved also through the use of sensor networks and the development of techniques to generate the map of an unknown environment.
Monitoring posture of the assisted person at discrete level (e.g., “standing”, or “sitting”).
To recognize the posture and/or the transition between postures (including a fall) it is possible to use wearable sensors incorporated in accessories (for example, but not limited to, watches and/or tags and/or eyeglasses and/or belts) and/or clothes.
Such wearable sensors require using algorithms for the detection and classification of postures, adaptable to the monitored person.
This case requires the presence of microphones and speakers in the devices, distributed and/or wearable.
The system according to the present invention can use, or interface, technologies for voice interaction, even commercially available, in particular to activate communication in response to specific events and/or emergency situations.
The voice interaction can be further integrated with the proactive analysis of situations, and techniques of the so-called “speech recognition” and “speech production”.
To these basic features some advanced features and options can be added such as, for example, the following one:
Thanks to this feature it is possible to integrate the functionalities described above with an analysis of the activity compared with models of cognitive impairments or other disabilities, based on the monitoring data of the daily activities of the said person and on comparison with behavioural models adapted to the person, in order to identify deviations from the normative behaviour models.
In this case it is also possible to perform an adaptation in time of the monitoring schemes (e.g., to evaluate the degradation over time of the person's physical, neurological and cognitive functions).
This additional functionality includes the steps of adaptation of customized standard models to the monitored person to new behaviour patterns in carrying out usual activities, and/or of identifying new activities, which vary over time.
Thanks to possible learning mechanisms described in literature, such as for example classifiers and predictive algorithms, it is possible to obtain new and/or updated models from sensory data, and to adapt the monitoring system according to the present invention to the progressive degradation over time of the person's physical, neurological and cognitive functions.
Step 300 represents the environment in which the assisted or monitored user. In step 310 the data collected are acquired by one or more sensors. The step 320 provides for the interpretation of these data in accordance with a behavioural model.
The step 330 provides classification of the type and quality of data collected in relation to the behavioural model. In this case the database of normative data, the description of the environment and of dialogue models is marked with tag 340 and includes descriptions of the behavioural model. When the classification does not detect dangerous or abnormal behaviour, the acquisition process continues. In case of abnormal behaviour a dialogue is triggered with the assisted person, from which information is obtained by the dialog models based on the identification of the behavioural condition or of the specific behavioural tipology.
If the classification detects a condition of danger at the step 350, an alarm is generated (marked 360). Otherwise the classification continues with the data acquisition cycle.
| Number | Date | Country | Kind |
|---|---|---|---|
| 102016000011204 | Feb 2016 | IT | national |
| Filing Document | Filing Date | Country | Kind |
|---|---|---|---|
| PCT/IB2017/050604 | 2/3/2017 | WO | 00 |
