CN102488495A - Digitalized intelligent evaluation method for nicotine dependence - Google Patents
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- CN102488495A CN102488495A CN2011104278281A CN201110427828A CN102488495A CN 102488495 A CN102488495 A CN 102488495A CN 2011104278281 A CN2011104278281 A CN 2011104278281A CN 201110427828 A CN201110427828 A CN 201110427828A CN 102488495 A CN102488495 A CN 102488495A
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Abstract
The invention provides a digitalized intelligent evaluation method for nicotine dependence. The digitalized intelligent evaluation method comprises the following steps of: (1) arranging an acceleration transducer for acquiring dynamic acceleration data of arms during smoking continuously at a wrist of a testee; (2) processing the acquired data, judging whether the smoking action is formed or not, recording moments corresponding to all smoking actions, and calculating an instant smoking speed; (3) performing fitting analysis by using a fold catastrophe model of a preset threshold value according to the recorded moments and the instant smoking speed, and performing fitting judgment to generate a corresponding nicotine dependence degree signal; and (4) outputting a result in a digitalized mode. According to the digitalized intelligent evaluation method, the data relevant to smoking trends is acquired by utilizing the acceleration transducer fixed to the wrist of the testee; and the acquired data is identified, processed, analyzed by the fold catastrophe model and subjected to result judgment automatically. The evaluation method has the characteristic of no wounds, and is quick, accurate, digitalized and intelligent.
Description
Technical field
The present invention relates to a kind of digital intelligent nicotine dependence assessment method, be specially a kind of acceleration transducer that utilizes and obtain data, automatically judgment processing data, analytical data, wired and nicotine dependence evaluating method that wirelessly transmitting data, intelligent data show automatically automatically.
Background technology
The harm of Nicotiana tabacum L. is universally acknowledged, but the people who smokes only increases, and there is 1,100,000,000 smoker in the whole world at present, and these data are all increasing progressively every year.Everybody knows " Smoking is harmful to your health ", but wants smoking cessation, and Easier said than done.We have to admit, owing to the serious consequence that smoking causes, have become one of human health to threaten greatly.Report according to American Cancer Society: the U.S. has 150,000 people to get killed because of smoking every year approximately; Show according to the investigation of World Health Organization (WHO): the people that the whole world is died from the smoking relevant disease every year reaches 4,000,000, will reach 1,000 ten thousand people to the year two thousand twenty expectation.
A large amount of harmful substances of handling up continuously, not only infringement is own healthy but also endangered other people.Show that according to World Health Organization's report smoking can cause disease more than 25 kinds; Long-term smoker will have common people to die from the middle age; Inhale a cigarette and can reduce by 8-11 minute life; And the probability that the smoker gets cancers such as coronary heart disease, pulmonary carcinoma, oral cancer, laryngeal carcinoma, esophageal carcinoma, gastric cancer, bladder cancer exceeds much than the non-smoker, and the cigarette amount is big more, and the danger of suffering from these cancers is high more.According to World Health Organization's statistics, the new cases of global annual pulmonary carcinoma surpass 1,200,000, about 1,100,000 people of number that therefore get killed every year.World Health Organization (WHO) estimates, smoking cessation, health diet, physical training and protect from infection and can prevent all types of cancers in the whole world 40%.Nicotiana tabacum L. is a most important preventible risk factor in the cancer.In order to help people's smoking cessation of smoking, whether the doctor at first will diagnose the people of a smoking habit-forming, and nicotine is produced the degree that relies on, just can take appropriate Therapeutic Method.
At present; Used test and appraisal diagnostic method and deficiency thereof: at present to the habit-forming two kind test and appraisal diagnostic methods the most authoritative of smoking with the diagnosis of nicotine dependence; A kind of is world health organisation recommendations " international morbidity statistics classification " the tenth edition (ICD-10)), another kind is that " mental sickness diagnostic & statistical manual " the 4th edition (DSM-IV) recommends in American Psychiatric Association.But these two kinds of methods are some impressions about smoking of the oral report of people by smoking fully, do not use objective indicator.Whether some objective indicator like the content that can give repeated exhortations in the concentration of carbon monoxide in the breath and the blood, can judge whether a people inhaled cigarette, but but can't diagnose habit-forming.
Therefore, more objective, quick, accurate, a reliable nicotine dependence assessment method being provided, to overcome the existing existing problem of method, is problem that needs to be resolved hurrily of medicine and hygiene fields and IT field.
Summary of the invention
Shortcoming and defect in view of above-mentioned existing diagnostic techniques; Technical problem to be solved by this invention is: a kind of digitized intelligent nicotine dependence test and appraisal technical method is provided, can nicotine dependence and degree of dependence can carry out noinvasive, quick, objective, accurately, test and appraisal reliably.
For achieving the above object and other purposes, nicotine dependence digital intelligent test and appraisal technical method provided by the present invention, it comprises: a kind of digital intelligent nicotine dependence assessment method, this method may further comprise the steps:
(1) acceleration transducer is set at testee's wrist place and is used for continuous acquisition arm dynamic acceleration information when smoking;
(2) data of gathering are handled and judged the action of whether smoking, if then write down smokings all in the smoking process and move the corresponding moment, and calculate instantaneous smoking speed;
(3) move the corresponding moment and instantaneous smoking speed according to all smokings in the smoking process of record, the folding catastrophic model of using predetermined threshold value carries out Fitting Analysis; And match is judged to produce corresponding nicotine dependence level signal;
(4) digitized result output.
Preferably, said step (2) comprising:
2-1: the data to acceleration transducer collects are carried out pretreatment, and the unlatching enumerator picks up counting;
2-2: to the smoke judgement of operating state of the data of finishing step 2-1; When the data that collect satisfy the condition that begins the state of smoking, then think to have got into to begin the smoking stage, and continue the judgement of succeeding state; Otherwise, restart the judgement that whole smoking is moved;
2-3: begin then judge whether meet the smoking state after the smoking stage judge to finish above-mentioned, satisfy the state of the action of smoking when the data that collect and judge, then think to have got into the smoking stage, otherwise, restart the judgement of whole smoking action;
2-4: after the 2-3 step end of above-mentioned smoking stage, then judge whether meet preparation end smoking state, prepare to finish the state judgement that smoking is moved, think that then this process is the action of smoking, and write down the current moment when the data that collect are satisfied.
Preferably, the data that among the step 2-1 acceleration transducer collected are carried out pretreatment and are meant that employing recurrence average filtering algorithm carries out the preliminary treatment operation of filtering and noise reduction.
Preferably, instantaneous smoking speed is the smoking number of times on the interval of action of smoking in the said step (2), that is to say that the used time of each smoking action is reciprocal.
Preferably, said step (3) is to handle also match through following steps to judge to produce corresponding nicotine dependence level signal:
5-1: the smoking moment and instantaneous smoking speed to collecting are carried out folding catastrophic model Fitting Analysis;
5-2: in the Fitting Analysis of the folding catastrophic model of step 5-1; If curve model is in preset folding catastrophic model number scope; Think that then being in this folding catastrophic model match judges the stage; And carry out follow-up match and judge, otherwise, then think to begin to carry out for the first time dependence degree folding catastrophic model match judgement and return execution in step (5-1);
5-3: after judgement is in the folding catastrophic model match judgement stage, constantly brings each group smoking into the folding catastrophic model and carry out Fitting Analysis, and obtain thus in the instantaneous smoking speed of the smoking of sampling time;
5-4: after the instantaneous smoking speed of the smoking that completing steps 5-3 is obtained at sampling time; The smoking speed of instantaneous smoking speed of calculating and collection is carried out difference relatively; If difference is less than preset threshold value; Think that then the smoking speed of gathering is fit to this folding catastrophic model, and carry out follow-up Fitting Analysis; Otherwise, then think once not to be fit to this folding catastrophic model, and return execution in step 5-3;
5-5: be fit to the determining step 5-4 completion of this folding catastrophic model in above-mentioned collection smoking speed after; If at most once be not fit to preset folding catastrophic model in the instantaneous smoking speed of all collections, think that then match is correct, then carry out follow-up judgement; Otherwise; Then think not to be fit to preset folding catastrophic model, continue the judgement of next folding catastrophic model, promptly carry out step 5-2;
Then, carry out step 5-6: in step 5-6, think to belong to this nicotine dependence rank, and folding catastrophic model Fitting Analysis begins to judge from first model next time.
Preferably; Preset folding catastrophic model is different nicotine dependence degree to be carried out rank divide in the said step (3), and its preset nicotine dependence degree model is set to the degree of dependence rank of 4 grades: not addiction, slight addiction, moderate addiction and severe addiction.
Preferably, said folding catastrophic model is meant that the speed Y of smoking is expressed as the function of time t:
Y＝at
2-bt+c
Wherein, c representes initial smoking speed, and a representes acceleration component, and b representes deceleration component.
Than prior art, the present invention has following advantage: and (1) objective-and present technique relies on the data of objective collection fully; (2) fast-exhausting (a few minutes) completion in the A Cigarette Without You; (3) digitized-present technique is diagnosed based on the folding catastrophic model of mathematics, and (4) intelligent-accomplish Data Management Analysis automatically; (5) automatization-all processes is accomplished automatically.
Can develop the instrument of the degree of judging whether the testee is addicted and is addicted according to this programme.Testing result can directly show at display, also can send through wired or wireless transmission means.
Description of drawings
Fig. 1 is the operating process sketch map of digital intelligent nicotine dependence assessment method of the present invention;
Fig. 2 is the concrete execution in step sketch map of the step S11 among Fig. 1;
Fig. 3 is the concrete execution in step sketch map of the step S12 among Fig. 1;
Fig. 4 a-4d is four kinds of different nicotine dependence degree folding catastrophic model figure.
[main element symbol description]
S10～S13 step
S110～S114 step
S120～S125 step
The specific embodiment
Below through specific instantiation embodiment of the present invention is described, those skilled in the art can understand other advantages of the present invention and effect easily by the content that this description disclosed.The present invention can also implement or use through the other different specific embodiment, and each item details in this description also can be based on different viewpoints and application, carries out various modifications or change under the spirit of the present invention not deviating from.
See also Fig. 1 to Fig. 4.Need to prove that the diagram that is provided in the present embodiment is only explained basic conception of the present invention in a schematic way.
Nicotine is to cause the habit-forming main cause of smoking.Addiction is more severe, and just big more to the instantaneous demand of nicotine, the speed of smoking is just fast more.The research of video recording smoking topology shows that habit-forming degree and instantaneous smoking speed (mouthful/minute) meet folding catastrophic model (Fold Catastrophe Model).
A kind of digital intelligent nicotine dependence of the present invention assessment method, this method may further comprise the steps:
(1) acceleration transducer is set at testee's wrist place and is used to gather arm dynamic acceleration information when smoking;
(2) according to corresponding dependency detection algorithm, judge the data that the collected action of whether smoking, write down in the smoking process all smokings and move the corresponding moment, calculate instantaneous smoking speed;
(3) use preset folding catastrophic model all data that collect are carried out Fitting Analysis, judge whether to be addicted, if judge the habit-forming degree that belongs to which degree according to drafting standard, making;
(4) result's output.
The people's of addiction instantaneous smoking speed meets the rule that experiment is found in the said step (1): the folding catastrophic model.During smoking, nicotine gets into brain through blood very soon, combines with nicotine receptor, lets the people produce happy sensation.Interaction between nicotine and the nicotine receptor meets biochemically balanced principle, and during beginning smoking, response speed is very fast, because a lot of free receptor.Along with the continuity of smoking time, the amount of free receptor descends rapidly, and the speed of therefore smoking also slows down thereupon.After nicotine and receptors bind played a role, these bonded nicotine receptors discharged again gradually, become free receptor.For satisfying the needs of the free receptor that these " usefulness " discharge again after crossing, the speed of smoking again can be from slowly to soon.
Experimental data shows that the people of nicotine dependence is arranged, and the speed of its smoking always near slowly, changes fast again then, not only meets the description of front, and also available folding catastrophic model comes quantitative description.
The detected person wears acceleration transducer at the wrist place in the said step (1).Through acceleration transducer, the continuous acquisition arm is dynamic acceleration information when smoking, and automatically data is carried out pretreatment.
The judgement of the action of whether smoking in the said step (2) is that the action algorithm of adopt smoking is realized, comprises the judgement of three states: begin to smoke, smoke and prepare to finish and smoke, three states occurred when continuous, then think the action of once smoking.
Concrete grammar is following:
(a) to the acceleration transducer collection and carry out pretreated data and carry out various states and judge; Begin the judgement of smoking state when data satisfy, then think to have got into to begin the smoking stage, and continue the judgement of succeeding state; Otherwise, restart the judgement that whole smoking is moved.
(b) begin after smoking stage (a) step finishes above-mentioned; Follow-up data are then judged the judgement that whether meets the smoking state; Satisfy the state of the action of smoking when data and judge, then think to have got into the smoking stage, then continue to accept the judgement of smoking state; Otherwise, restart the judgement that whole smoking is moved.
(c) after the above-mentioned smoking stage, (b) step finished, subsequent acquisition to data prepare to finish the judgement of the state of smoking, satisfy the state of the action of preparing to finish to smoke when data and judge, think that then this process is the action of smoking, and write down the current moment.
Said instantaneous smoking speed is the smoking number of times on the interval of action of smoking, and that is to say that the used time of each smoking action is reciprocal.
Above-mentioned whole process, all data of record be the detected person under required movement, all in the whole smoking process are smoked action constantly and instantaneous smoking speed.
Preset folding catastrophic model in the said step (3); Be according to the folding catastrophic model principle of finding; Different nicotine dependence degree are carried out rank divide, its preset nicotine dependence degree model is set to the degree of dependence rank of 4 grades: not addiction, slight addiction, moderate addiction and severe addiction.
After whole smoking process finishes, collect to such an extent that smoke and carry out the match judgement with instantaneous smoking speed constantly to all.If the smoking that collects is constantly followed the match of one of predeterminable level folding catastrophic model with instantaneous smoking speed in threshold range, then think this detected person's nicotine dependence degree, and belong to the degree of dependence rank of institute's match.
Concrete, as shown in Figure 1, it is for showing the operating process sketch map of digital intelligent nicotine dependence assessment method of the present invention.Below will combine Fig. 1 to Fig. 3 to specify the concrete operations step of nicotine dependence intelligent detecting method of the present invention.
At first, execution in step S10, the acceleration transducer continuous acquisition required about the dynamic data of smoking.The people of nicotine dependence to be detected wears the nicotine dependence intelligent detector on wrist; Acceleration transducer in the detector has adopted acceleration transducer; It is constantly sampled and the output acceleration information with certain frequency, the severe that the clear people's of these tables of data arm moves on certain direction.
Then, carry out step S11.
In step S11, the data of gathering are handled and judged the action of whether smoking, if, then write down the current moment, if not, follow-up judgement then continued.Particularly, seeing also Fig. 2, is the data of gathering are handled and to be judged through following steps: at first, in step S110, all acceleration informations that collect are carried out recurrence average filtering, and open enumerator and pick up counting; Then, to the smoke judgement of operating state of pretreated data, carry out the judgement of subsequent step; Carry out step S111, in step S111, pretreated data are judged whether begin the smoking state; If the data fit that collects begins the condition of the state of smoking, then carry out step S112, otherwise; Then think current and the action of smoking also occurs, and return execution in step S110; In step S112, pretreated data are judged the state of whether smoking, if the condition of the data fit smoking state that collects is then carried out step S113, otherwise, then think current and the action of smoking also occurs, and return execution in step S110; In step S113, pretreated data are judged whether prepare to finish the smoking state, if the condition of the data fit smoking state that collects; Then carry out step S114; Otherwise, then think current and the action of smoking also occurs, and return execution in step S110; Then, carry out step S114; In step S114, be judged as the action of smoking, and write down the current moment.What need explain is here, and the The data recurrence average filtering algorithm that acceleration collects carries out filtering, disturb to remove, because the technology that the recurrence average filtering algorithm is notified for those skilled in the art, so, be not described in detail in this.In addition, removing interferential method has a variety ofly, and therefore, acceleration information described here is removed interferential method and is not limited only to above-mentioned filtering method.Then, carry out step S12.
In step S12, after the whole process of smoking finishes,, judge fitting degree with preset nicotine dependence degree folding catastrophic model according to the smoking moment and the instantaneous smoking speed of storage.Particularly, seeing also Fig. 3, is to handle also match through following steps to judge to produce corresponding nicotine dependence level signal: at first; In step S120; The smoking moment and instantaneous smoking speed to collecting are carried out folding catastrophic model Fitting Analysis, then, and execution in step S121; In step 121; If curve model is in preset folding catastrophic model number scope; Think that then being in this folding catastrophic model match judges the stage; Then carry out step S122, otherwise, then think to begin to carry out for the first time dependence degree folding catastrophic model match judgement and return execution in step S120; In step S122, each group is smoked and constantly will be brought the folding catastrophic model into, and obtains thus in the instantaneous smoking speed of the smoking of sampling time; Then, carry out step S123; In step 123, the smoking speed of instantaneous smoking speed of calculating and collection is carried out difference relatively, if difference, thinks then that the smoking speed of gathering is fit to this folding catastrophic model less than preset threshold value, and carry out step S124; Otherwise, then think once not to be fit to this folding catastrophic model, and return execution in step S122; In step S124; If at most once be not fit to preset folding catastrophic model in the instantaneous smoking speed of all collections, think that then match is correct, then carry out step S125; Otherwise; Then think not to be fit to preset folding catastrophic model, continue the judgement of next folding catastrophic model, promptly carry out step S121; Then, carry out step S125, in step 125, think to belong to this degree of dependence, and folding catastrophic model Fitting Analysis begins to judge from first model next time.
Then, carry out step S13.
In step S13, in threshold range, satisfy the Fitting Analysis of one of folding catastrophic model, then think to belong to this nicotine dependence rank, and export with digitized forms.Particularly, be to determine testing result to belong to not addiction in the nicotine dependence degree rank of four grades, slightly addiction, moderate addiction and severe addiction according to above-mentioned match situation with the rule folding catastrophic model of finding.
The folding catastrophic model Fitting Analysis and the relevant parameter thereof of nicotine dependence and instantaneous smoking speed are explained as follows:
The research of video recording smoking topology shows, according to the folding catastrophic model, if people's smoking is habit-forming, nicotine has been produced dependence, and the speed Y of its smoking (several mouthfuls of per minute smokings) can be expressed as the function of time t:
Y＝at
2-bt+c
In the formula, c representes initial smoking speed, and a representes acceleration component, and b representes deceleration component.Parameter a and b and nicotine dependence are closely related.
Accompanying drawing 4 has provided the data analysis result that the people of four smokings obtains through video recording.ID representes the numbering that four differences are tried among the figure; R2 representes the goodness that cooperates of observed data and folding catastrophic model.In four are tried, the a=1.94 of ID#:1, b=5.08 and cooperation goodness R2=0.99 are the highest." mental sickness diagnostic & statistical manual " the 4th edition (DSM-IV) of contrast American Psychiatric Association, this is tried the nicotine dependence degree also is the highest, in the symptom of 12 nicotine dependences enumerated, possesses 7 kinds.The a=0.51 of ID#:8, b=-0.17 and cooperation goodness R2=0.69 are minimum." mental sickness diagnostic & statistical manual " the 4th edition (DSM-IV) of contrast American Psychiatric Association, this is tried nicotine-free and is relied on, and in the symptom of 12 nicotine dependences enumerated, a kind of do not have yet.
In sum; The present invention is through finding different nicotine dependence degree; On instantaneous smoking speed, be fit to different folding catastrophic models, and adopt the acceleration transducer collection and judge smoking action and smoking constantly, cooperate the different nicotine dependence degree folding catastrophic models of being found; According to actual acquisition situation and the match situation of finding the folding catastrophic model, realize detection to different nicotine dependence degree.And the present invention comes out except being used to gather the intelligent acceleration transducer of acceleration, without any need for other external equipment, avoided in the prior art in order to realize that nicotine dependence detects, and the expensive defective that causes.Moreover; The present invention has good real-time and intelligent; The detected person carries intelligent acceleration transducer on wrist, after the whole process of smoking finishes, intelligent acceleration transducer can according to collect the real-time output nicotine dependence degree rank of data message.
The foregoing description is illustrative principle of the present invention and effect thereof only, but not is used to limit the present invention.Any be familiar with this technological personage all can be under spirit of the present invention and category, the foregoing description is modified or is changed.Therefore, have common knowledge the knowledgeable in the affiliated such as technical field, must contain by claim of the present invention not breaking away from all equivalence modifications of being accomplished under disclosed spirit and the technological thought or changing.
Claims (7)
1. digital intelligent nicotine dependence assessment method, it is characterized in that: this method may further comprise the steps:
(1) acceleration transducer is set at testee's wrist place and is used for continuous acquisition arm dynamic acceleration information when smoking;
(2) data of gathering are handled and judged the action of whether smoking, if then write down smokings all in the smoking process and move the corresponding moment, and calculate instantaneous smoking speed;
(3) move the corresponding moment and instantaneous smoking speed according to all smokings in the smoking process of record, the folding catastrophic model of using predetermined threshold value carries out Fitting Analysis, and match is judged to produce corresponding nicotine dependence level signal;
(4) digitized result output.
2. digital intelligent nicotine dependence assessment method according to claim 1 is characterized in that, said step (2) comprising:
2-1: the data to acceleration transducer collects are carried out pretreatment, and the unlatching enumerator picks up counting;
2-2: to the smoke judgement of operating state of the data of finishing step 2-1; When the data that collect satisfy the condition that begins the state of smoking, then think to have got into to begin the smoking stage, and continue the judgement of succeeding state; Otherwise, restart the judgement that whole smoking is moved;
2-3: begin then judge whether meet the smoking state after the smoking stage judge to finish above-mentioned, satisfy the state of the action of smoking when the data that collect and judge, then think to have got into the smoking stage, otherwise, restart the judgement of whole smoking action;
2-4: after above-mentioned smoking stage 2-3 step finishes; Then judge whether meet preparation end smoking state, prepare to finish the state judgement that smoking is moved, think that then this process is the action of smoking when the data that collect are satisfied; Write down the current moment, and calculate instantaneous smoking speed.
3. digital intelligent nicotine dependence assessment method according to claim 2; It is characterized in that the data that among the step 2-1 acceleration transducer collected are carried out pretreatment and are meant that employing recurrence average filtering algorithm carries out the preliminary treatment operation of filtering and noise reduction.
4. digital intelligent nicotine dependence assessment method according to claim 1 is characterized in that, instantaneous smoking speed is the smoking number of times on the interval of action of smoking in the said step (2), that is to say that the used time of each smoking action is reciprocal.
5. digital intelligent nicotine dependence assessment method according to claim 1 is characterized in that, said step (3) is to handle also match through following steps to judge to produce corresponding nicotine dependence level signal:
5-1: the smoking moment and instantaneous smoking speed to collecting are carried out folding catastrophic model Fitting Analysis;
5-2: in the Fitting Analysis of the folding catastrophic model of step 5-1; If curve model is in preset folding catastrophic model number scope; Think that then being in this folding catastrophic model match judges the stage; And carry out follow-up match and judge, otherwise, then think to begin to carry out for the first time dependence degree folding catastrophic model match judgement and return execution in step 5-1;
5-3: after judgement is in the folding catastrophic model match judgement stage, constantly brings each group smoking into the folding catastrophic model and carry out Fitting Analysis, and obtain thus in the instantaneous smoking speed of the smoking of sampling time;
5-4: after the instantaneous smoking speed of the smoking that completing steps 5-3 is obtained at sampling time; The smoking speed of instantaneous smoking speed of calculating and collection is carried out difference relatively; If difference is less than preset threshold value; Think that then the smoking speed of gathering is fit to this folding catastrophic model, and carry out follow-up Fitting Analysis; Otherwise, then think once not to be fit to this folding catastrophic model, and return execution in step 5-3;
5-5: be fit to the determining step 5-4 completion of this folding catastrophic model in above-mentioned collection smoking speed after; If at most once be not fit to preset folding catastrophic model in the instantaneous smoking speed of all collections, think that then match is correct, then carry out follow-up judgement; Otherwise; Then think not to be fit to preset folding catastrophic model, continue the judgement of next folding catastrophic model, promptly carry out step 5-2;
Then, carry out step 5-6:, in step 5-6, think to belong to this nicotine dependence rank, and folding catastrophic model Fitting Analysis begins to judge from first model next time.
6. digital intelligent nicotine dependence assessment method according to claim 5; It is characterized in that; Preset folding catastrophic model is different nicotine dependence degree to be carried out rank divide in the said step (3), and its preset nicotine dependence degree model is set to the degree of dependence rank of 4 grades: not addiction, slight addiction, moderate addiction and severe addiction.
7. digital intelligent nicotine dependence assessment method according to claim 1 is characterized in that, said folding catastrophic model is meant that the speed Y of smoking is the function of time t:
Y＝at
2-bt+c
Wherein, c representes initial smoking speed, and a representes acceleration component, and b representes deceleration component.
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| CN110122929A (en) * | 2019-05-17 | 2019-08-16 | 南京大学 | A kind of smoking event monitoring system and monitoring method based on inertial sensor |
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN104127242A (en) * | 2014-07-17 | 2014-11-05 | 东软熙康健康科技有限公司 | Method and device for identifying smoking behavior |
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| CN110122929A (en) * | 2019-05-17 | 2019-08-16 | 南京大学 | A kind of smoking event monitoring system and monitoring method based on inertial sensor |
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